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Conference: Gordon Research Conference on Batteries-Ventura

NSF

01/15/2024

06/30/2024

{'Value': 'Standard Grant'}

{'Code': '07020000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'CBET', 'LongName': 'Div Of Chem, Bioeng, Env, & Transp Sys'}}

{'SignBlockName': 'Carole Read', 'PO_EMAI': 'cread@nsf.gov', 'PO_PHON': '7032922418'}

This award will provide partial support for the 2024 Gordon Research Conference (GRC) on Batteries, to be held in Ventura, CA on February 25-March 1, 2024. The GRC will provide significant professional development activities for graduate students and post doctoral research fellows in the area of electrochemical energy storage. The GRC will also stimulate new advances in batteries for renewable energy storage through interaction of scientists and engineers who are both new and established in this field.<br/><br/>The technical challenges of understanding and improving current electrochemical energy storage systems, which include batteries, require a collaborative effort from researchers in many disciplines. There are still many fundamental gaps in understanding the atomic- and molecular-level processes that determine and govern the function, operation, performance limitations, and failure of battery systems. Fundamental knowledge is critically needed to uncover the underlying principles that control these complex and interrelated processes. With this underpinning knowledge, wholly new concepts in materials design can be developed for producing electrodes, electrolytes, and battery cells that are capable of storing higher energy densities and have long cycle lifetimes, at lower cost. The conference will cover topics related to solid state batteries, next generation batteries, advanced characterization, battery recycling, and policy and techno- economics. The theme of the GRC on batteries highlights theory, materials synthesis, and engineering concepts under the umbrella of the conference.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

01/23/2024

01/23/2024

None

Grant

47.041, 47.049

1

4900

4900

2415014

{'FirstName': 'Kelsey', 'LastName': 'Hatzell', 'PI_MID_INIT': 'B', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Kelsey B Hatzell', 'EmailAddress': 'kelsey.hatzell@princeton.edu', 'NSF_ID': '000721734', 'StartDate': '01/23/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Princeton University', 'CityName': 'PRINCETON', 'ZipCode': '085442001', 'PhoneNumber': '6092583090', 'StreetAddress': '1 NASSAU HALL', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'New Jersey', 'StateCode': 'NJ', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_ORG': 'NJ12', 'ORG_UEI_NUM': 'NJ1YPQXQG7U5', 'ORG_LGL_BUS_NAME': 'THE TRUSTEES OF PRINCETON UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Princeton University', 'CityName': 'PRINCETON', 'StateCode': 'NJ', 'ZipCode': '085442001', 'StreetAddress': '1 NASSAU HALL', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'New Jersey', 'CountryFlag': '1', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_PERF': 'NJ12'}

[{'Code': '1762', 'Text': 'SOLID STATE & MATERIALS CHEMIS'}, {'Code': '7644', 'Text': 'EchemS-Electrochemical Systems'}]

2024~20000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2415014.xml'}

SBIR Phase I: ADAPTIVE PERIMETRY FOR HEAD MOUNTED DEVICES

NSF

08/01/2024

04/30/2025

{'Value': 'Standard Grant'}

{'Code': '15030000', 'Directorate': {'Abbreviation': 'TIP', 'LongName': 'Dir for Tech, Innovation, & Partnerships'}, 'Division': {'Abbreviation': 'TI', 'LongName': 'Translational Impacts'}}

{'SignBlockName': 'Alastair Monk', 'PO_EMAI': 'amonk@nsf.gov', 'PO_PHON': '7032924392'}

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is the development of a novel tool for the diagnosis and monitoring of functional visual field (VF) defects due to glaucoma. Glaucoma, a leading cause of blindness, is asymptomatic in its early stages and challenging to diagnose, often resulting in late detection. 3 million Americans have a diagnosis of glaucoma, and this number is expected to double by 2050 contributing to a market size for treatment exceeding $7 billion by 2028. Early identification of disease and disease progression is key in preventing vision loss. Using a novel testing method, this technology will capture VF changes with higher sensitivity and specificity than the current standard of care. If successful, the proposed solution will allow for earlier detection of glaucoma and glaucomatous progression and facilitate earlier clinical intervention by eye care providers, reducing the overall burden of disease and incidence of irreversible vision loss.    <br/>   <br/>This Small Business Innovation Research Phase I project aims to improve the early detection of vision loss due to glaucoma through the development of fully automated adaptive perimetry software. Conventional VF testing, known as static automated perimetry (SAP), lacks sensitivity, often leading to late diagnosis of glaucoma and irreversible vision loss. With SAP, defects can only be detected when they affect at least 3 degrees of the visual field, providing only a macro understanding of vision loss. This project aims to develop a fully automated adaptive perimetry test that combines the uniformity and standardization of SAP with greater precision and individualization of an adaptive test strategy. This novel testing algorithm will intelligently adjust stimuli based on individual responses, increasing the sensitivity and specificity of early defect detection, and mapping functional deficits to retinal anatomical defects. Objectives include mathematical modeling of the retinal pathophysiology of glaucoma, development of spatial analysis for real-time test location determination, development of methods for active correction of fixational errors using eye-tracking, and determination of suprathreshold contrasts. <br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

07/24/2024

07/24/2024

None

Grant

47.084

1

4900

4900

2415015

{'FirstName': 'Lama', 'LastName': 'Al-Aswad', 'PI_MID_INIT': 'A', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Lama A Al-Aswad', 'EmailAddress': 'lalaswad@envisionhealthtech.com', 'NSF_ID': '000867954', 'StartDate': '07/24/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'ENVISION HEALTH TECHNOLOGIES INC', 'CityName': 'BRONXVILLE', 'ZipCode': '107085003', 'PhoneNumber': '9176238517', 'StreetAddress': '16 STURGIS RD', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'New York', 'StateCode': 'NY', 'CONGRESSDISTRICT': '16', 'CONGRESS_DISTRICT_ORG': 'NY16', 'ORG_UEI_NUM': 'Y2HZLWDKEDZ1', 'ORG_LGL_BUS_NAME': 'ENVISION HEALTH TECHNOLOGIES INC', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'ENVISION HEALTH TECHNOLOGIES INC', 'CityName': 'Brooklyn', 'StateCode': 'NY', 'ZipCode': '112261786', 'StreetAddress': '760 Parkside Ave', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'New York', 'CountryFlag': '1', 'CONGRESSDISTRICT': '09', 'CONGRESS_DISTRICT_PERF': 'NY09'}

{'Code': '537100', 'Text': 'SBIR Phase I'}

2024~275000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2415015.xml'}

I-Corps: Translation potential of semiautomatic segmentation of cardiac tomography images for myocardial blood flow quantification

NSF

05/01/2024

04/30/2025

{'Value': 'Standard Grant'}

{'Code': '15030000', 'Directorate': {'Abbreviation': 'TIP', 'LongName': 'Dir for Tech, Innovation, & Partnerships'}, 'Division': {'Abbreviation': 'TI', 'LongName': 'Translational Impacts'}}

{'SignBlockName': 'Jaime A. Camelio', 'PO_EMAI': 'jcamelio@nsf.gov', 'PO_PHON': '7032922061'}

The broader impact of this I-Corps project is the development of a novel analytic software tool incorporated with a semi-automatic algorithm for the segmentation of cardiac tomography images. The tool will be used to non-invasively quantify myocardial blood flow and flow reserve. This software tool provides a user-friendly image processing mechanism with minimal user intervention and thus, has less variability in quantitative results than other existing commercial software. The current practice of manually drawing regions of interest introduces inter-operator and intra-operator variability and may suffer from relatively low reproducibility between operators. The quantitative analytic tool can be utilized to assess myocardial blood flow and reserve not only for dynamic cardiac positron emission tomography, but potentially for dynamic cardiac single photon emission computed tomography.<br/><br/>This I-Corps project utilizes experiential learning coupled with a first-hand investigation of the industry ecosystem to assess the translation potential of the technology. This solution is based on the development of a semi-automatic approach to define the regions of interest of the myocardial and blood pool volumes and to segment myocardial edges from dynamic cardiac tomography images to improve the accuracy and precision of myocardial blood flow and reserve quantification. The semi-automatic method is based on a novel scheme referred as to the triple-factor non-negative matrix factorization. This method is used for dynamic tomography image segmentation of the left ventricle, from which the time activity curves of the left ventricle myocardium and cavity are extracted and used in the kinetic modeling for calculating the myocardial blood flow and reserve. The quantitative software tool incorporated with the semi-automatic segmentation approach has been verified with computer simulations and validated with a large cohort of clinical patients.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

04/19/2024

04/19/2024

None

Grant

47.084

1

4900

4900

2415021

{'FirstName': 'Yi-Hwa', 'LastName': 'Liu', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Yi-Hwa Liu', 'EmailAddress': 'yi-hwa.liu@yale.edu', 'NSF_ID': '000991175', 'StartDate': '04/19/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Yale University', 'CityName': 'NEW HAVEN', 'ZipCode': '065113572', 'PhoneNumber': '2037854689', 'StreetAddress': '150 MUNSON ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Connecticut', 'StateCode': 'CT', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_ORG': 'CT03', 'ORG_UEI_NUM': 'FL6GV84CKN57', 'ORG_LGL_BUS_NAME': 'YALE UNIV', 'ORG_PRNT_UEI_NUM': 'FL6GV84CKN57'}

{'Name': 'YALE UNIVERSITY SCHOOL OF MEDICINE', 'CityName': 'NEW HAVEN', 'StateCode': 'CT', 'ZipCode': '065118917', 'StreetAddress': '333 Cedar Street', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Connecticut', 'CountryFlag': '1', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_PERF': 'CT03'}

{'Code': '802300', 'Text': 'I-Corps'}

2024~50000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2415021.xml'}

Building Cybersecurity Analytics Capacity in Big Data Era: Developing Hands-on Labs for Integrating Data Science into Cybersecurity Curriculum

NSF

10/01/2023

08/31/2024

{'Value': 'Standard Grant'}

{'Code': '11010000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DGE', 'LongName': 'Division Of Graduate Education'}}

{'SignBlockName': 'Li Yang', 'PO_EMAI': 'liyang@nsf.gov', 'PO_PHON': '7032922677'}

Given the wide-spread use of big data, there is a growing need to develop a cyber-workforce that understands cybersecurity in the context of big data. The goal of this project from the University of North Texas is to integrate data science into cybersecurity curriculum and train the next generation of security experts. The project proposes to have direct and long-term impacts on the growing national need for highly-trained cybersecurity professionals with data analytics capabilities, by increasing the number and quality of cybersecurity analysts. This project aims to develop instructional materials that cater to a wide-range of student learning styles. The materials will be designed so that educators at a wide-range of institutions (e.g., community college to research-intensive institutions), and with varying levels of cybersecurity knowledge, can easily incorporate them into their instruction.<br/><br/>The proposed project seeks to develop a set of instructional modules and hands-on labs that make use of state-of-the-art data analytics for addressing different cybersecurity challenges. These instructional modules will follow active learning principles designed to engage students, regardless of learning style, and ensure that students retain the content learned. The modules will be based on real-world security systems and will be designed to systematically cover fundamental security principles. This approach will allow students to get exposure to data analytics techniques and their application to cybersecurity challenges via real-world examples. The project aims to produce engaging materials that could be easily adopted by other educators. To simplify integration and encourage adoption, the hands-on labs will be built based on only open source software and tools that are free to use for educational purposes. Further, they will be distributed via virtual machine images that already contain all libraries and required software to run the labs. This approach for development will allow a variety of instructors to confidently integrate state-of-the-art data analytics labs into curriculum with minimal effort.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

02/20/2024

02/20/2024

None

Grant

47.076

1

4900

4900

2415022

{'FirstName': 'Daniel', 'LastName': 'Takabi', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Daniel Takabi', 'EmailAddress': 'takabi@odu.edu', 'NSF_ID': '000658609', 'StartDate': '02/20/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Old Dominion University Research Foundation', 'CityName': 'NORFOLK', 'ZipCode': '235082561', 'PhoneNumber': '7576834293', 'StreetAddress': '4111 MONARCH WAY', 'StreetAddress2': 'STE 204', 'CountryName': 'United States', 'StateName': 'Virginia', 'StateCode': 'VA', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_ORG': 'VA03', 'ORG_UEI_NUM': 'DSLXBD7UWRV6', 'ORG_LGL_BUS_NAME': 'OLD DOMINION UNIVERSITY RESEARCH FOUNDATION', 'ORG_PRNT_UEI_NUM': 'DSLXBD7UWRV6'}

{'Name': 'Old Dominion University Research Foundation', 'CityName': 'NORFOLK', 'StateCode': 'VA', 'ZipCode': '235290001', 'StreetAddress': '5115 Hampton Blvd', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Virginia', 'CountryFlag': '1', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_PERF': 'VA03'}

{'Code': '166800', 'Text': 'CYBERCORPS: SCHLAR FOR SER'}

2018~56334

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2415022.xml'}

Elucidating the role of carrier transport layers on perovskite photovoltaics' stability through automated experimentation and a machine-learning-assisted analysis

NSF

10/01/2024

09/30/2027

{'Value': 'Standard Grant'}

{'Code': '07010000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'ECCS', 'LongName': 'Div Of Electrical, Commun & Cyber Sys'}}

{'SignBlockName': 'Prem Chahal', 'PO_EMAI': 'pchahal@nsf.gov', 'PO_PHON': '7032920000'}

Despite recent clean-energy initiatives, the US currently ranks second in global yearly total CO2 emission, totaling 5.01 billion metric tons in 2022. As such, developing stable and low-cost solar cells is critical. An emerging class of material, named halide perovskites, have the potential to deliver high-performing and low-cost solar cells or be combined with silicon, which dominates ~90% of the market, to boost performance. However, device degradation under environmental stressors (e.g., humidity, oxygen, and temperature) still precludes their commercialization. Concomitantly, the implementation of low-cost polymer materials to help collecting the current produced by the devices while securing long lifetime is urgently needed. Therefore, a primary research goal of this project is to advance the state-of-knowledge of halide perovskite solar cells by developing high-performance devices with enhanced stability upon exposure to environmental stressors. The methodology to be implemented combines automated experiments with a machine learning driven analysis that will help identifying polymers that can enhance device stability and performance. Broadly, the research component of this project will impact the development of future solar cells by resolving the ideal combination of stressors. The outreach impacts will help female students securing leading positions in STEM by provide mentoring and training, including research experiences to graduate and undergraduate students. The Materials Science and Engineering at UC Davis curriculum will be enhanced by adding new lectures into a core course for undergraduates. All ML codes will be made available in GitHub and the scientific findings will be disseminated through peer-reviewed publications. <br/><br/>This research aims to investigate three challenges related to HP solar cells: (1) determine the combined effects of environmental stressors on perovskites’ stability; (2) quantify hole transport material/halide perovskite (HTM/HP) interface stability using novel, state-of-the-art conducting polymers that enable matching the energetics of band alignment required for high-performing photovoltaics; and (3) demonstrate solar cells with >95% performance retention for >1,000 h. Because controlled stability tests conventionally require extremely time-consuming tasks, automated and high-throughput experiments will be used. The information acquired will, in turn, inform machine learning algorithms to forecast stable HTM/HP interfaces. First, in situ optical measurements will be performed under distinct environmental conditions to elucidate the individual and combined effects of humidity, oxygen, and temperature on HP degradation. Second, the HPs will be interrogated via in situ X-ray diffraction to resolve how structural changes correlate with and affect device performance. Third, the effects of the abovementioned stressors on the HTM/HP interfaces using six cutting-edge, novel HTMs will be quantified while gathering valuable data for training machine learning algorithms. Fourth, this information will identify the most stable HTM/HP interfaces through predictive, physics-informed models. The results generated will guide the future development of application-dependent encapsulation strategies for HP solar cells with prolonged lifetime.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/01/2024

08/01/2024

None

Grant

47.041

1

4900

4900

2415023

{'FirstName': 'Marina', 'LastName': 'Leite', 'PI_MID_INIT': 'S', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Marina S Leite', 'EmailAddress': 'mleite@ucdavis.edu', 'NSF_ID': '000667705', 'StartDate': '08/01/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'University of California-Davis', 'CityName': 'DAVIS', 'ZipCode': '956186153', 'PhoneNumber': '5307547700', 'StreetAddress': '1850 RESEARCH PARK DR STE 300', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'California', 'StateCode': 'CA', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_ORG': 'CA04', 'ORG_UEI_NUM': 'TX2DAGQPENZ5', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF CALIFORNIA, DAVIS', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'University of California-Davis', 'CityName': 'DAVIS', 'StateCode': 'CA', 'ZipCode': '956165270', 'StreetAddress': 'One Shields Avenue', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'California', 'CountryFlag': '1', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_PERF': 'CA04'}

{'Code': '151700', 'Text': 'EPMD-ElectrnPhoton&MagnDevices'}

2024~425000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2415023.xml'}

Supporting Student Mechanistic Reasoning Through Scaffolded Task Design and Generative AI Feedback

NSF

10/01/2024

09/30/2027

{'Value': 'Standard Grant'}

{'Code': '11040000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DUE', 'LongName': 'Division Of Undergraduate Education'}}

{'SignBlockName': 'Dawn Rickey', 'PO_EMAI': 'drickey@nsf.gov', 'PO_PHON': '7032924674'}

As understanding of the world becomes ever more complex, it is important that people understand how and why phenomena occur, rather than simply knowing that they occur. For example, understanding why a large unvaccinated population is more likely to give rise to mutations in viral infections, or why polyfluorinated alkyl substances (PFAS) are so difficult to remove from drinking water, are the first steps in addressing such problems. Thus, it is important to support undergraduate students in learning to construct mechanistic explanations and models to explain how and why things happen. Students who engage in these activities are more likely to learn deeply and be able to use their knowledge in new situations. Thus, helping students engage in mechanistic reasoning will not only support students as they work to connect relevant ideas, but will also provide evidence about the depth and interconnectivity of student understanding. This project aims to serve the national interest by determining how to support large numbers of undergraduate chemistry students as they construct mechanistic explanations and models, particularly in large introductory courses that often act as a barrier to Science, Technology, Engineering, and Mathematics (STEM) success. To achieve this goal, the project team will design tasks that have the potential to elicit student explanations about how and why phenomena occur. Students’ responses to such tasks are typically time consuming for instructors to grade, and particularly as the phenomena become more complex, it may become difficult for students to connect all the ideas involved. To provide support for these complex tasks, the project team will train and implement generative artificial intelligence (AI) chatbots to provide feedback to students. It is expected that these chatbots will be able to accurately characterize students’ responses and provide feedback in a variety of ways, including in the form of a Socratic dialogue.<br/><br/>Evidence suggests that having undergraduate students construct mechanistic explanations in the context of formative tasks is an equitable approach to instruction for courses that typically function as a gateway to STEM careers. To achieve equitable instruction, it is important to support students as they regularly engage with tasks designed to extend and connect their knowledge. Thus, the project team from Michigan State University (MSU) will implement a modified evidence-centered design process to determine both the cognitive and epistemic resources students need to construct mechanistic explanations and to articulate the evidence of understanding expected to be elicited for a range of complex tasks. Using those design specifications, generative AI feedback systems will be designed to support students’ knowledge construction and knowledge use. The AI chatbots will be implemented in general chemistry courses at MSU and the project team will characterize the ways in which students’ learning and perceptions of learning are impacted by interacting with the chatbots. These findings will be used to develop a framework for the design of explanation tasks involving complex phenomena and the accompanying AI feedback systems to best support students. Results of the investigations have the potential to transform STEM courses by advancing knowledge of how to design and engineer instructional tasks that both provide opportunities to connect and use knowledge and provide richer insights into what students know and can do. The NSF IUSE: EDU Program supports research and development projects to improve the effectiveness of STEM education for all students. Through its Engaged Student Learning track, the program supports the creation, exploration, and implementation of promising practices and tools.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/15/2024

08/15/2024

None

Grant

47.076

1

4900

4900

2415032

{'FirstName': 'Melanie', 'LastName': 'Cooper', 'PI_MID_INIT': 'M', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Melanie M Cooper', 'EmailAddress': 'mmc@msu.edu', 'NSF_ID': '000257059', 'StartDate': '08/15/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Michigan State University', 'CityName': 'EAST LANSING', 'ZipCode': '488242600', 'PhoneNumber': '5173555040', 'StreetAddress': '426 AUDITORIUM RD RM 2', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Michigan', 'StateCode': 'MI', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_ORG': 'MI07', 'ORG_UEI_NUM': 'R28EKN92ZTZ9', 'ORG_LGL_BUS_NAME': 'MICHIGAN STATE UNIVERSITY', 'ORG_PRNT_UEI_NUM': 'VJKZC4D1JN36'}

{'Name': 'Michigan State University', 'CityName': 'EAST LANSING', 'StateCode': 'MI', 'ZipCode': '488242600', 'StreetAddress': '426 AUDITORIUM RD RM 2', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Michigan', 'CountryFlag': '1', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_PERF': 'MI07'}

{'Code': '199800', 'Text': 'IUSE'}

2024~399432

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2415032.xml'}

Non-Born-Oppenheimer Effects in the Framework of Multicomponent Time-Dependent Density Functional Theory

NSF

01/15/2024

07/31/2024

{'Value': 'Continuing Grant'}

{'Code': '03090000', 'Directorate': {'Abbreviation': 'MPS', 'LongName': 'Direct For Mathematical & Physical Scien'}, 'Division': {'Abbreviation': 'CHE', 'LongName': 'Division Of Chemistry'}}

{'SignBlockName': 'Richard Dawes', 'PO_EMAI': 'rdawes@nsf.gov', 'PO_PHON': '7032927486'}

Professor Sharon Hammes-Schiffer of Yale University is supported by an award from the Chemical Theory, Models and Computational Methods program in the Division of Chemistry to develop computational methods for describing the role of electrons and protons in chemical processes. The interaction or coupling of electrons and protons plays a vital role in a wide range of biological and chemical processes, including photosynthesis, respiration, and energy production in solar cells. The development of computational methods that accurately describe this coupling is challenging because electrons and protons are so light that they must be treated specially, which is computationally expensive. Professor Hammes-Schiffer is developing methods that describe electrons and protons in a computationally practical manner. She is applying these methods to specific processes of biological and chemical relevance to elucidate the fundamental principles of these processes. In addition, she and her research group are incorporating these computational methods into established quantum chemistry software packages to benefit the general scientific community. Professor Hammes-Schiffer is also maintaining and enhancing a website containing software and educational tools including computer programs, tools, demonstrations, and tutorials. This research facilitates technological and biomedical advances in more effective solar cells and other renewable energy sources as well as improved understanding of enzymes. <br/><br/>Professor Hammes-Schiffer is developing new theoretical and computational approaches that provide insight into the underlying fundamental principles of photoinduced proton transfer and proton-coupled electron transfer (PCET) reactions, which play a vital role in a broad range of biological and chemical processes. These approaches are designed to include nuclear quantum effects, such as proton delocalization and zero-point energy, as well as non-Born-Oppenheimer effects, in a computationally practical manner. Hammes-Schiffer is developing these methods within the framework of the nuclear-electronic orbital density functional theory (NEO-DFT) approach, which treats key nuclei, such as the transferring proton(s), quantum mechanically on the same level as the electrons within the framework of DFT. The multicomponent time-dependent DFT (NEO-TDDFT) approach enables the calculation of excited electronic, proton vibrational, and electron-proton vibronic states. Hammes-Schiffer is developing NEO methods for computing minimum energy paths and tunneling splittings for proton transfer and PCET reactions, as well as mixed electron-proton vibronic excited states for photoinduced reactions. She is also developing real-time NEO-TDDFT methods and other nonadiabatic dynamics methods for the simulation of ultrafast electronic and nuclear dynamics, targeting applications to photoinduced PCET reactions. She is incorporating these approaches into well-established quantum chemistry software packages and is creating tutorials to explain how to perform NEO calculations and highlight the unique capabilities of this approach. Furthermore, she is maintaining and enhancing a web site on PCET to convey useful information to the community and to provide valuable tools, scripts, and programs relevant to studying PCET.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

01/05/2024

01/05/2024

None

Grant

47.049

1

4900

4900

2415034

{'FirstName': 'Sharon', 'LastName': 'Hammes-Schiffer', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Sharon Hammes-Schiffer', 'EmailAddress': 'shs566@princeton.edu', 'NSF_ID': '000154996', 'StartDate': '01/05/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Princeton University', 'CityName': 'PRINCETON', 'ZipCode': '085442001', 'PhoneNumber': '6092583090', 'StreetAddress': '1 NASSAU HALL', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'New Jersey', 'StateCode': 'NJ', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_ORG': 'NJ12', 'ORG_UEI_NUM': 'NJ1YPQXQG7U5', 'ORG_LGL_BUS_NAME': 'THE TRUSTEES OF PRINCETON UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Princeton University', 'CityName': 'PRINCETON', 'StateCode': 'NJ', 'ZipCode': '085442001', 'StreetAddress': '1 NASSAU HALL', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'New Jersey', 'CountryFlag': '1', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_PERF': 'NJ12'}

{'Code': '688100', 'Text': 'Chem Thry, Mdls & Cmptnl Mthds'}

2021~314583

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2415034.xml'}

EAGER SENTINELS: The PCR-free Biosensor for a Fast, Simple, and Sensitive Detection of RNA.

NSF

01/01/2024

01/31/2025

{'Value': 'Standard Grant'}

{'Code': '07020000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'CBET', 'LongName': 'Div Of Chem, Bioeng, Env, & Transp Sys'}}

{'SignBlockName': 'Aleksandr Simonian', 'PO_EMAI': 'asimonia@nsf.gov', 'PO_PHON': '7032922191'}

The recent pandemic has highlighted the urgent need for rapid and accurate detection of viruses to allow for early disease diagnosis and monitoring to prevent future pandemics and to reduce the risk of complications and mortality through timely health care. Currently, diagnostic tests based on polymerase chain reaction (PCR) are widely applied for the detection of viruses. Despite outstanding analytical parameters, significant drawbacks of this technology have become evident during the recent COVID pandemic. More specifically, PCR-based tests require not only expensive laboratory equipment and highly trained personnel, but they are also time-consuming and not well adapted for point-of-care devices. For example, it usually takes two to three days to get the result of a PCR-based COVID-19 test. Consequently, the spread of the virus becomes less containable. The purpose of this project is to develop a fast, easy, and economically feasible biosensing platform that does not require PCR. This project also aims to provide undergraduate students with interdisciplinary training in the development of biosensors, and local high school students with an opportunity to explore the field of diagnostics.<br/><br/>This project is to design and realize a rapid, ultrasensitive, and adaptable PCR-free biosensing platform for viral RNA detection. Specifically, the proposed biosensor will be based on the newly discovered CRISPR-Cas (Clustered Regularly Interspaced Short Palindromic Repeat – CRISPR associated) nuclease that shows high selectivity, and can be reprogrammed to detect various viruses’ RNAs. The development and integrations of a novel signal amplification scheme will allow circumvention of the PCR amplification step. Not only will this research lead to the novel RNA sensing approach, but it will also provide a blueprint for developing a DNA biosensor based on an alternative but closely related Cas nuclease. Due to the ease of configuration and operation, the proposed biosensor is more economical, faster, and will not require sophisticated equipment and personnel training, thereby addressing current needs in public health.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

01/08/2024

01/08/2024

None

Grant

47.041

1

4900

4900

2415037

{'FirstName': 'Artavazd', 'LastName': 'Badalyan', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Artavazd Badalyan', 'EmailAddress': 'a.badalyan@usu.edu', 'NSF_ID': '000844251', 'StartDate': '01/08/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'University of Louisiana at Lafayette', 'CityName': 'LAFAYETTE', 'ZipCode': '705032014', 'PhoneNumber': '3374825811', 'StreetAddress': '104 E UNIVERSITY AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Louisiana', 'StateCode': 'LA', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_ORG': 'LA03', 'ORG_UEI_NUM': 'C169K7T4QZ96', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF LOUISIANA AT LAFAYETTE', 'ORG_PRNT_UEI_NUM': 'C169K7T4QZ96'}

{'Name': 'University of Louisiana at Lafayette', 'CityName': 'LAFAYETTE', 'StateCode': 'LA', 'ZipCode': '705032014', 'StreetAddress': '104 E UNIVERSITY CIR 3RD FL', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Louisiana', 'CountryFlag': '1', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_PERF': 'LA03'}

{'Code': '790900', 'Text': 'BIOSENS-Biosensing'}

['2021~14834', '2022~29151']

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2415037.xml'}

RUI: Studies of Nucleon Structure at Jefferson Lab

NSF

08/15/2024

07/31/2027

{'Value': 'Standard Grant'}

{'Code': '03010000', 'Directorate': {'Abbreviation': 'MPS', 'LongName': 'Direct For Mathematical & Physical Scien'}, 'Division': {'Abbreviation': 'PHY', 'LongName': 'Division Of Physics'}}

{'SignBlockName': 'Allena K. Opper', 'PO_EMAI': 'aopper@nsf.gov', 'PO_PHON': '7032928958'}

It is now a well-established fact that nucleons (protons and neutrons) are made up of more elementary constituents - quarks and gluons. The main physics program supported by this award aims to study the internal structure of the proton and neutron. More specifically, this research group will scatter electrons from protons and neutrons at Jefferson Laboratory to measure the electric and magnetic properties of the nucleon. The group is involved in these efforts through the design of new experiments, the construction of advanced particle detectors, and the development of novel analysis, modeling, and data acquisition software. The faculty involve students in research by providing meaningful, substantive projects to both undergraduate and graduate students.<br/><br/>The group’s long established program of experiments embody Jefferson Lab’s fundamental mission: to elucidate the underlying structure of protons, neutrons, and mesons. They focus on experiments that will further our understanding of the quark spin structure of the proton and neutron in the non-perturbative regime. Jefferson Lab’s high-intensity polarized 12 GeV electron beam provides the opportunity for an increased physics reach; indeed, the group continues to lead efforts to extend the measurements of the proton and neutron electromagnetic form factors to the highest momentum transfers possible at Jefferson Lab, and also investigate possible modification of the proton form factor ratio within the nuclear medium. These experiments provide severe tests of the available theoretical models of nucleon structure, and at the same time serve as an impetus for the development of new and more advanced models based on Quantum Chromo-Dynamics (QCD).<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/07/2024

08/07/2024

None

Grant

47.049

1

4900

4900

2415038

[{'FirstName': 'Edward', 'LastName': 'Brash', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Edward Brash', 'EmailAddress': 'edward.brash@cnu.edu', 'NSF_ID': '000481386', 'StartDate': '08/07/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'David', 'LastName': 'Heddle', 'PI_MID_INIT': 'P', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'David P Heddle', 'EmailAddress': 'david.heddle@cnu.edu', 'NSF_ID': '000507590', 'StartDate': '08/07/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]

{'Name': 'Christopher Newport University', 'CityName': 'NEWPORT NEWS', 'ZipCode': '236063072', 'PhoneNumber': '7575947392', 'StreetAddress': '1 AVENUE OF THE ARTS', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Virginia', 'StateCode': 'VA', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_ORG': 'VA03', 'ORG_UEI_NUM': 'VMYDF2TZHHB6', 'ORG_LGL_BUS_NAME': 'CHRISTOPHER NEWPORT UNIVERSITY', 'ORG_PRNT_UEI_NUM': 'VMYDF2TZHHB6'}

{'Name': 'Christopher Newport University', 'CityName': 'Newport News', 'StateCode': 'VA', 'ZipCode': '236063072', 'StreetAddress': '1 Avenue of the Arts', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Virginia', 'CountryFlag': '1', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_PERF': 'VA03'}

{'Code': '123200', 'Text': 'Nuclear & Hadron Quantum Chrom'}

2024~570000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2415038.xml'}

Collaborative Research: Understanding the effects of solvents on the adsorption energies of prototypical reactants on catalyst surfaces

NSF

09/15/2024

08/31/2027

{'Value': 'Standard Grant'}

{'Code': '07020000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'CBET', 'LongName': 'Div Of Chem, Bioeng, Env, & Transp Sys'}}

{'SignBlockName': 'Robert McCabe', 'PO_EMAI': 'rmccabe@nsf.gov', 'PO_PHON': '7032924826'}

The design of new, more active, and selective catalysts is vital for creating cleaner, more sustainable chemical processes with wide-ranging applications, including renewable energy and chemical syntheses. A typical catalytic process includes multiple elementary steps involving many surface-bound intermediates and transition states. The energetics of these intermediates and transition states are crucial, as they determine the rate and selectivity of the catalysts, yet accurate energies are only available for a few key intermediates on metals. The project will use Single Crystal Adsorption Calorimetry (SCAC) to directly measure the heat of adsorption and co-adsorption with solvents on clean single-crystal surfaces in an ultrahigh vacuum. Graduate students and postdocs involved in this project will benefit from the learning and professional environment at PNNL. Microcalorimetry will also be integrated into a mini research project for high school students attending Summer Experience in Science and Engineering for Youth at Oregon State University.<br/><br/>SCAC provides the only way to measure the heat of adsorption for irreversible events like dissociative adsorption, which are crucial for producing adsorbed molecular fragments ubiquitous in catalytic mechanisms (e.g., -OH, -CH3, -OCH3, -OOCH) and part of the project. These measurements will also expand to include metal oxides (e.g., FeO/Pt(111). The adsorbate energies gained from these studies will provide fundamental information about the effects of solvents on the binding of reaction intermediates. They will further serve as benchmarks for more accurate theoretical predictions of adsorption energies and effects of solvent on their values, improving predictability and enabling computational catalysis design.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

07/10/2024

07/10/2024

None

Grant

47.041

1

4900

4900

2415040

{'FirstName': 'Liney', 'LastName': 'Arnadottir', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Liney Arnadottir', 'EmailAddress': 'liney.arnadottir@oregonstate.edu', 'NSF_ID': '000609023', 'StartDate': '07/10/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Oregon State University', 'CityName': 'CORVALLIS', 'ZipCode': '973318655', 'PhoneNumber': '5417374933', 'StreetAddress': '1500 SW JEFFERSON AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Oregon', 'StateCode': 'OR', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_ORG': 'OR04', 'ORG_UEI_NUM': 'MZ4DYXE1SL98', 'ORG_LGL_BUS_NAME': 'OREGON STATE UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Oregon State University', 'CityName': 'CORVALLIS', 'StateCode': 'OR', 'ZipCode': '973318655', 'StreetAddress': '1500 SW JEFFERSON AVE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Oregon', 'CountryFlag': '1', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_PERF': 'OR04'}

{'Code': '140100', 'Text': 'Catalysis'}

2024~362442

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2415040.xml'}

Collaborative Research: Understanding the effects of solvents on the adsorption energies of prototypical reactants on catalyst surfaces

NSF

09/15/2024

08/31/2027

{'Value': 'Standard Grant'}

{'Code': '07020000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'CBET', 'LongName': 'Div Of Chem, Bioeng, Env, & Transp Sys'}}

{'SignBlockName': 'Robert McCabe', 'PO_EMAI': 'rmccabe@nsf.gov', 'PO_PHON': '7032924826'}

The design of new, more active, and selective catalysts is vital for creating cleaner, more sustainable chemical processes with wide-ranging applications, including renewable energy and chemical syntheses. A typical catalytic process includes multiple elementary steps involving many surface-bound intermediates and transition states. The energetics of these intermediates and transition states are crucial, as they determine the rate and selectivity of the catalysts, yet accurate energies are only available for a few key intermediates on metals. The project will use Single Crystal Adsorption Calorimetry (SCAC) to directly measure the heat of adsorption and co-adsorption with solvents on clean single-crystal surfaces in an ultrahigh vacuum. Graduate students and postdocs involved in this project will benefit from the learning and professional environment at PNNL. Microcalorimetry will also be integrated into a mini research project for high school students attending Summer Experience in Science and Engineering for Youth at Oregon State University.<br/><br/>SCAC provides the only way to measure the heat of adsorption for irreversible events like dissociative adsorption, which are crucial for producing adsorbed molecular fragments ubiquitous in catalytic mechanisms (e.g., -OH, -CH3, -OCH3, -OOCH) and part of the project. These measurements will also expand to include metal oxides (e.g., FeO/Pt(111). The adsorbate energies gained from these studies will provide fundamental information about the effects of solvents on the binding of reaction intermediates. They will further serve as benchmarks for more accurate theoretical predictions of adsorption energies and effects of solvent on their values, improving predictability and enabling computational catalysis design.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

07/10/2024

07/10/2024

None

Grant

47.041

1

4900

4900

2415041

{'FirstName': 'Zdenek', 'LastName': 'Dohnalek', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Zdenek Dohnalek', 'EmailAddress': 'zdenek.dohnalek@wsu.edu', 'NSF_ID': '000989591', 'StartDate': '07/10/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Washington State University', 'CityName': 'PULLMAN', 'ZipCode': '991640001', 'PhoneNumber': '5093359661', 'StreetAddress': '240 FRENCH ADMINISTRATION BLDG', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Washington', 'StateCode': 'WA', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_ORG': 'WA05', 'ORG_UEI_NUM': 'XRJSGX384TD6', 'ORG_LGL_BUS_NAME': 'WASHINGTON STATE UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Washington State University', 'CityName': 'Richland', 'StateCode': 'WA', 'ZipCode': '993520999', 'StreetAddress': 'PO Box 999', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Washington', 'CountryFlag': '1', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_PERF': 'WA04'}

{'Code': '140100', 'Text': 'Catalysis'}

2024~211477

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2415041.xml'}

CAREER: User-Based Simulation Methods for Quantifying Sources of Error and Bias in Recommender Systems

NSF

10/01/2023

08/31/2025

{'Value': 'Continuing Grant'}

{'Code': '05020000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'IIS', 'LongName': 'Div Of Information & Intelligent Systems'}}

{'SignBlockName': 'Dan Cosley', 'PO_EMAI': 'dcosley@nsf.gov', 'PO_PHON': '7032928832'}

Systems that recommend products, places, and services are an increasingly common part of everyday life and commerce, making it important to understand how recommendation algorithms affect outcomes for both individual users and larger social groups. To do this, the project team will develop novel methods of simulating users' behavior based on large-scale historical datasets. These methods will be used to better understand vulnerabilities that underlying biases in training datasets pose to commonly-used machine learning-based methods for building and testing recommender systems, as well as characterize the effectiveness of common evaluation metrics such as recommendation accuracy and diversity given different models of how people interact with recommender systems in practice. The team will publicly release its datasets, software, and novel metrics for the benefit of other researchers and developers of recommender systems. The work also will inform the development of computer science course materials about the social impact of data analytics as well as outreach activities for librarians, who are often in the position of helping information seekers understand the way search engines and other recommender systems affect their ability to get what they need.<br/><br/>The work is organized around two main themes. The first will quantify and mitigate the popularity bias and misclassified decoy problems in offline recommender evaluation that tend to lead to popular, known recommendations. To do this, the team will develop simulation-based evaluation models that encode a variety of assumptions about how users select relevant items to buy and rate and use them to quantify the statistical biases these assumptions induce in recommendation quality metrics. They will calibrate these simulations by comparing with existing data sets covering books, research papers, music, and movies. These models and datasets will help drive the second main project around measuring the impact of feature distributions in training data on recommender algorithm accuracy and diversity, while developing bias-resistant algorithms. The team will use data resampling techniques along with the simulation models, extended to model system behavior over time, to evaluate how different algorithms mitigate, propagate, or exacerbate underlying distributional biases through their recommendations, and how those biased recommendations in turn affect future user behavior and experience.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

01/29/2024

01/29/2024

None

Grant

47.070

1

4900

4900

2415042

{'FirstName': 'Michael', 'LastName': 'Ekstrand', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Michael Ekstrand', 'EmailAddress': 'mde48@drexel.edu', 'NSF_ID': '000676745', 'StartDate': '01/29/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Drexel University', 'CityName': 'PHILADELPHIA', 'ZipCode': '191042875', 'PhoneNumber': '2158956342', 'StreetAddress': '3141 CHESTNUT ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Pennsylvania', 'StateCode': 'PA', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_ORG': 'PA03', 'ORG_UEI_NUM': 'XF3XM9642N96', 'ORG_LGL_BUS_NAME': 'DREXEL UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Drexel University', 'CityName': 'PHILADELPHIA', 'StateCode': 'PA', 'ZipCode': '191042816', 'StreetAddress': '3141 CHESTNUT ST', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Pennsylvania', 'CountryFlag': '1', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_PERF': 'PA03'}

{'Code': '736700', 'Text': 'HCC-Human-Centered Computing'}

2022~43597

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2415042.xml'}

Conference: Doctoral Consortium at Student Research Workshop at the Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)

NSF

05/01/2024

04/30/2025

{'Value': 'Standard Grant'}

{'Code': '05020000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'IIS', 'LongName': 'Div Of Information & Intelligent Systems'}}

{'SignBlockName': 'Eleni Miltsakaki', 'PO_EMAI': 'emiltsak@nsf.gov', 'PO_PHON': '7032922972'}

This grant provides funds to support participation in the Student Research Workshop in the Computational Linguistics at the North America Association for Computational Linguistics (NAACL) 2024 Conference during the period of July 16-21 in Mexico City, Mexico. The ACL is the primary international organization in the field of natural language processing and language engineering. The Student Research Workshop (SRW) is an established tradition at ACL conferences, allowing students to present their research, experience a global conference in their field of, and receive invaluable feedback from senior researchers. <br/><br/>The intellectual merit of this award is that it enables doctoral students to exchange insights and receive feedback and guidance. The workshop format is a stimulating environment for students to present their work and be exposed to outside perspectives at a critical time in their research career. The Student Research Workshop welcomes two types of submissions: research papers and thesis proposals. The feedback that students receive from other students and faculty members helps them enhance their own dissertation research proposals. The broader impact of this grant is that it facilitates new research collaborations and professional networks, as well as developing a greater awareness of ongoing cutting-edge research.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

04/15/2024

04/15/2024

None

Grant

47.070

1

4900

4900

2415059

{'FirstName': 'Marcos', 'LastName': 'Zampieri', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Marcos Zampieri', 'EmailAddress': 'mzampier@gmu.edu', 'NSF_ID': '000864654', 'StartDate': '04/15/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'George Mason University', 'CityName': 'FAIRFAX', 'ZipCode': '220304422', 'PhoneNumber': '7039932295', 'StreetAddress': '4400 UNIVERSITY DR', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Virginia', 'StateCode': 'VA', 'CONGRESSDISTRICT': '11', 'CONGRESS_DISTRICT_ORG': 'VA11', 'ORG_UEI_NUM': 'EADLFP7Z72E5', 'ORG_LGL_BUS_NAME': 'GEORGE MASON UNIVERSITY', 'ORG_PRNT_UEI_NUM': 'H4NRWLFCDF43'}

{'Name': 'George Mason University', 'CityName': 'FAIRFAX', 'StateCode': 'VA', 'ZipCode': '220304422', 'StreetAddress': '4400 UNIVERSITY DR', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Virginia', 'CountryFlag': '1', 'CONGRESSDISTRICT': '11', 'CONGRESS_DISTRICT_PERF': 'VA11'}

{'Code': '749500', 'Text': 'Robust Intelligence'}

2024~20000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2415059.xml'}

Collaborative Research: New Regression Models and Methods for Studying Multiple Categorical Responses

NSF

01/15/2024

08/31/2025

{'Value': 'Continuing Grant'}

{'Code': '03040000', 'Directorate': {'Abbreviation': 'MPS', 'LongName': 'Direct For Mathematical & Physical Scien'}, 'Division': {'Abbreviation': 'DMS', 'LongName': 'Division Of Mathematical Sciences'}}

{'SignBlockName': 'Yong Zeng', 'PO_EMAI': 'yzeng@nsf.gov', 'PO_PHON': '7032927299'}

In many areas of scientific study including bioengineering, epidemiology, genomics, and neuroscience, an important task is to model the relationship between multiple categorical outcomes and a large number of predictors. In cancer research, for example, it is crucial to model whether a patient has cancer of subtype A, B, or C and high or low mortality risk given the expression of thousands of genes. However, existing statistical methods either cannot be applied, fail to capture the complex relationships between the response variables, or lead to models that are difficult to interpret and thus, yield little scientific insight. The PIs address this deficiency by developing multiple new statistical methods. For each new method, the PIs will provide theoretical justifications and fast computational algorithms. Along with graduate and undergraduate students, the PIs will also create publicly available software that will enable applications across both academia and industry.<br/><br/>This project aims to address a fundamental problem in multivariate categorical data analysis: how to parsimoniously model the joint probability mass function of many categorical random variables given a common set of high-dimensional predictors. The PIs will tackle this problem by using emerging technologies on tensor decompositions, dimension reduction, and both convex and non-convex optimization. The project focuses on three research directions: (1) a latent variable approach for the low-rank decomposition of a conditional probability tensor; (2) a new overlapping convex penalty for intrinsic dimension reduction in a multivariate generalized linear regression framework; and (3) a direct non-convex optimization-based approach for low-rank tensor regression utilizing explicit rank constraints on the Tucker tensor decomposition. Unlike the approach of regressing each (univariate) categorical response on the predictors separately, the new models and methods will allow practitioners to characterize the complex and often interesting dependencies between the responses.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

01/26/2024

01/26/2024

None

Grant

47.049

1

4900

4900

2415067

{'FirstName': 'Aaron', 'LastName': 'Molstad', 'PI_MID_INIT': 'J', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Aaron J Molstad', 'EmailAddress': 'amolstad@umn.edu', 'NSF_ID': '000845253', 'StartDate': '01/26/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'University of Minnesota-Twin Cities', 'CityName': 'MINNEAPOLIS', 'ZipCode': '554552009', 'PhoneNumber': '6126245599', 'StreetAddress': '200 OAK ST SE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Minnesota', 'StateCode': 'MN', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_ORG': 'MN05', 'ORG_UEI_NUM': 'KABJZBBJ4B54', 'ORG_LGL_BUS_NAME': 'REGENTS OF THE UNIVERSITY OF MINNESOTA', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'University of Minnesota-Twin Cities', 'CityName': 'MINNEAPOLIS', 'StateCode': 'MN', 'ZipCode': '554552009', 'StreetAddress': '200 OAK ST SE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Minnesota', 'CountryFlag': '1', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_PERF': 'MN05'}

{'Code': '126900', 'Text': 'STATISTICS'}

['2022~13790', '2023~53590']

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2415067.xml'}

Solar Eclipse Workshop: Observations of April 2024 Total Solar Eclipse and Community Discussion of Multi-Scale Coupling in Geospace Environment; Arlington, Texas; April 8-10, 2024

NSF

02/01/2024

01/31/2025

{'Value': 'Standard Grant'}

{'Code': '06020200', 'Directorate': {'Abbreviation': 'GEO', 'LongName': 'Directorate For Geosciences'}, 'Division': {'Abbreviation': 'AGS', 'LongName': 'Div Atmospheric & Geospace Sciences'}}

{'SignBlockName': 'Shikha Raizada', 'PO_EMAI': 'sraizada@nsf.gov', 'PO_PHON': '7032928963'}

Solar eclipse event on April 8, 2024, provides an excellent opportunity to scientists for engaging in outreach efforts and to investigate the influence of reduction in the ionizing source on our Earth’s atmosphere. This workshop intends to organize educational activities at the University of Texas at Arlington (UTA), which is on the path of totality. It means that the moon completely obscures the sun and for this event in April, the totality will last for about 4 minutes. This short period of darkness offers a direct observing window where people can observe solar corona using safety goggles and collect data using scientific instruments. Scientists at UTA plan to take advantage of the upcoming solar eclipse and will use their state-of the-art Planetariums and telescopes to create public awareness and bring K-12 students to these facilities.<br/><br/>The scientific workshop will be held for two days between April 8 – 10, 2024. Prior to this event, several activities are planned to enable proper dissemination of information about the solar eclipse to K-12 students. The team will distribute educational materials and safety goggles by visiting different schools in the area between March 18 – 31, 2024. Technical support from International Astronomical Union (IAU) to facilitate observations using UTA telescopes and their access to public is also planned. This workshop will promote inter-disciplinary collaborations, encourage interactions between students and space-scientists. UTA will host several scientific instruments to address questions about (a) the spatial and temporal variability of Corona during totality and (b) response of the ionosphere-thermosphere system to solar eclipse? To investigate the first topic, use of professional four Maxvision ED80 telescopes (narrowband) and two spectral telescopes in a relative broad wavelength will be used. Several GNSS receivers will be used to explore the effects of solar eclipse on the Earth’s ionosphere-thermosphere region. This grant is in response to NSF 23-014, “Dear Colleague letter: Great American Solar Eclipses 2023 and 2024” to support science, education and outreach activities related to Solar Eclipses.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

01/16/2024

01/16/2024

None

Grant

47.050

1

4900

4900

2415082

[{'FirstName': 'Zihan', 'LastName': 'Wang', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Zihan Wang', 'EmailAddress': 'zihan.wang@uta.edu', 'NSF_ID': '000901085', 'StartDate': '01/16/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Yue', 'LastName': 'Deng', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Yue Deng', 'EmailAddress': 'yuedeng@uta.edu', 'NSF_ID': '000531943', 'StartDate': '01/16/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Nilakshi', 'LastName': 'Veerabathina', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Nilakshi Veerabathina', 'EmailAddress': 'nilakshi@uta.edu', 'NSF_ID': '000991500', 'StartDate': '01/16/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'LEVENT', 'LastName': 'GURDEMIR', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'LEVENT GURDEMIR', 'EmailAddress': 'gurdemir@uta.edu', 'NSF_ID': '000991554', 'StartDate': '01/16/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]

{'Name': 'University of Texas at Arlington', 'CityName': 'ARLINGTON', 'ZipCode': '760199800', 'PhoneNumber': '8172722105', 'StreetAddress': '701 S NEDDERMAN DR', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Texas', 'StateCode': 'TX', 'CONGRESSDISTRICT': '25', 'CONGRESS_DISTRICT_ORG': 'TX25', 'ORG_UEI_NUM': 'LMLUKUPJJ9N3', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF TEXAS AT ARLINGTON', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'University of Texas at Arlington', 'CityName': 'ARLINGTON', 'StateCode': 'TX', 'ZipCode': '760199800', 'StreetAddress': '701 S. NEDDERMAN DR', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Texas', 'CountryFlag': '1', 'CONGRESSDISTRICT': '25', 'CONGRESS_DISTRICT_PERF': 'TX25'}

{'Code': '152100', 'Text': 'AERONOMY'}

2024~49999

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2415082.xml'}

The Geological Context of Hominin Fossils

NSF

08/15/2024

07/31/2026

{'Value': 'Standard Grant'}

{'Code': '04040000', 'Directorate': {'Abbreviation': 'SBE', 'LongName': 'Direct For Social, Behav & Economic Scie'}, 'Division': {'Abbreviation': 'BCS', 'LongName': 'Division Of Behavioral and Cognitive Sci'}}

{'SignBlockName': 'John Yellen', 'PO_EMAI': 'jyellen@nsf.gov', 'PO_PHON': '7032928759'}

This project focuses on one of the most pressing questions in the study of human evolution, the replacement of Neanderthals by modern humans. Neanderthals, who evolved in Europe and were established there for over 200,000 years, vanished from the fossil record shortly after modern humans entered the area approximately 50,000 years ago. Current explanations for Neanderthals' disappearance center on their inability to compete with modern humans, who had symbolic culture and more advanced technologies. Yet, genetic evidence shows that the two populations made contact and interbred. What was the nature of this contact? Archaeological evidence to answer this question is present at one archaeological site. Fossilized bones of Neanderthals and modern humans have been found in the same stratigraphic layer, meaning that the two populations were contemporaneous. However, some evidence suggests that the modern human fossils may be younger and accidentally became incorporated into an older layer. The focus of this project is to apply numerous scientific techniques to test whether the fossils were deposited at the same time or not. If contemporaneity is confirmed, this site will be the first to provide direct archaeological evidence of the period of interaction when modern humans and Neanderthals met. In addition to answering the scientific questions, the project will train students in cutting-edge methods of archaeological excavation and analysis and provide field as well as lab-based research opportunities for undergraduate and graduate students. Career-building opportunities abound. Undergraduate students needing fieldwork to get jobs or get into graduate school gain valuable skills through their participation in the project. Graduate students' theses benefit from their access to first-class research materials, and networking opportunities with scientists from the U.S. and other countries will expand their job prospects.<br/><br/>This project helps to clarify a crucial period within human evolution. The site is likely one of the earliest sites where such contact occurred. In order to test the contemporaneity of the Neanderthal and modern human fossils, specialists examine the preservation of the bones, radiocarbon date them, and attempt to extract DNA from them. The geological stratigraphy of the site is studied using microscopic and chemical analytical techniques. All of these analyses are necessary to confirm the rare discovery that modern humans and Neanderthals were present at the same time, in the same rockshelter.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/08/2024

08/08/2024

None

Grant

47.075

1

4900

4900

2415087

[{'FirstName': 'Gilbert', 'LastName': 'Tostevin', 'PI_MID_INIT': 'B', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Gilbert B Tostevin', 'EmailAddress': 'toste003@umn.edu', 'NSF_ID': '000440072', 'StartDate': '08/08/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Gilliane', 'LastName': 'Monnier', 'PI_MID_INIT': 'F', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Gilliane F Monnier', 'EmailAddress': 'monni003@umn.edu', 'NSF_ID': '000637447', 'StartDate': '08/08/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}]

{'Name': 'University of Minnesota-Twin Cities', 'CityName': 'MINNEAPOLIS', 'ZipCode': '554552009', 'PhoneNumber': '6126245599', 'StreetAddress': '200 OAK ST SE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Minnesota', 'StateCode': 'MN', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_ORG': 'MN05', 'ORG_UEI_NUM': 'KABJZBBJ4B54', 'ORG_LGL_BUS_NAME': 'REGENTS OF THE UNIVERSITY OF MINNESOTA', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'University of Minnesota-Twin Cities', 'CityName': 'MINNEAPOLIS', 'StateCode': 'MN', 'ZipCode': '554552009', 'StreetAddress': '395 Humphrey Center', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Minnesota', 'CountryFlag': '1', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_PERF': 'MN05'}

{'Code': '139100', 'Text': 'Archaeology'}

2024~270229

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2415087.xml'}

Robot-induced personalized ground stiffness perturbations for long-term gait adaptation and rehabilitation after stroke

NSF

08/01/2024

07/31/2027

{'Value': 'Standard Grant'}

{'Code': '07020000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'CBET', 'LongName': 'Div Of Chem, Bioeng, Env, & Transp Sys'}}

{'SignBlockName': 'Amanda O. Esquivel', 'PO_EMAI': 'aesquive@nsf.gov', 'PO_PHON': '7032920000'}

This project addresses the critical challenge of improving gait rehabilitation for stroke survivors, who often face long-term disabilities that significantly impact their quality of life. Current rehabilitation methods, which are typically repetitive and generic, offer limited effectiveness. This research introduces an innovative robotic intervention using the Variable Stiffness Treadmill 2 (VST 2), which can adjust the walking surface's stiffness to enhance balance, propulsion, and symmetry in gait. By developing a comprehensive and personalized gait model, the project aims to tailor rehabilitation strategies to individual characteristics, potentially revolutionizing gait therapy with long-lasting benefits. The project's broader impacts include advancing our understanding of motor adaptation and learning in human gait, which can be applied to various fields such as orthotics, prosthetics, and robotic walkers. Additionally, the research will establish practical guidelines for clinical settings to improve stroke rehabilitation outcomes. The project also emphasizes education and training for underrepresented high school and college students through annual design competitions and summer internships, fostering diversity in the field. All generated materials and models will be openly shared with the scientific community, promoting reproducibility and further research. <br/><br/>The primary goal of this project is to enhance post-stroke gait recovery by improving balance, propulsion, and symmetry. The scope of the project includes utilizing the Variable Stiffness Treadmill 2 (VST 2), which introduces unilateral and bilateral perturbations to the walking surface's vertical stiffness. Using a Nonlinear Model Predictive Control (NR-MPC) approach, a multi-layer neuromuscular model that captures long-term motor adaptations in human gait will be developed. This model will guide the creation of personalized intervention protocols tailored to individual patient characteristics. Methodologically, the project will involve testing the VST 2 and the neuromuscular model on both healthy subjects and hemiplegic stroke survivors. For stroke patients, the model will be customized to generate optimized perturbations aimed at promoting specific long-term rehabilitation outcomes. These interventions will be evaluated on stroke subjects, focusing on metrics such as increased propulsion, improved balance, and enhanced gait symmetry. The potential contributions of this project to science and engineering include a deeper understanding of motor adaptation and learning in human gait, advancements in personalized rehabilitation techniques, and the development of innovative technologies applicable to orthotics, prosthetics, and robotic assistance devices. This research has the potential to significantly impact clinical practices and improve the quality of life for individuals with gait impairments.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

07/15/2024

07/15/2024

None

Grant

47.041

1

4900

4900

2415093

{'FirstName': 'Panagiotis', 'LastName': 'Artemiadis', 'PI_MID_INIT': 'K', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Panagiotis K Artemiadis', 'EmailAddress': 'partem@udel.edu', 'NSF_ID': '000610322', 'StartDate': '07/15/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'University of Delaware', 'CityName': 'NEWARK', 'ZipCode': '197160099', 'PhoneNumber': '3028312136', 'StreetAddress': '220 HULLIHEN HALL', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Delaware', 'StateCode': 'DE', 'CONGRESSDISTRICT': '00', 'CONGRESS_DISTRICT_ORG': 'DE00', 'ORG_UEI_NUM': 'T72NHKM259N3', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF DELAWARE', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'University of Delaware', 'CityName': 'NEWARK', 'StateCode': 'DE', 'ZipCode': '197160099', 'StreetAddress': '220 HULLIHEN HALL', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Delaware', 'CountryFlag': '1', 'CONGRESSDISTRICT': '00', 'CONGRESS_DISTRICT_PERF': 'DE00'}

{'Code': '534200', 'Text': 'Disability & Rehab Engineering'}

2024~486830

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2415093.xml'}

Understanding electronic transport and dynamics of quantum-dot-doped-semiconductor solids for infrared optoelectronics

NSF

08/15/2024

07/31/2027

{'Value': 'Continuing Grant'}

{'Code': '03070000', 'Directorate': {'Abbreviation': 'MPS', 'LongName': 'Direct For Mathematical & Physical Scien'}, 'Division': {'Abbreviation': 'DMR', 'LongName': 'Division Of Materials Research'}}

{'SignBlockName': 'Paul Lane', 'PO_EMAI': 'plane@nsf.gov', 'PO_PHON': '7032922453'}

Nontechnical Description<br/><br/>Quantum dots (QDs) are nanocrystals with optical properties that depend on their size and composition. This makes it possible to tune their absorption and emission spectra from the visible to the infrared region for desired applications. For example, quantum dots emitting precise colored light have been used as emissive layers in displays with high definition and saturated colors. However, their implementation in electronic devices is limited by poor charge transport properties. This research focuses on developing and understanding a novel hybrid system that integrates QDs into high-mobility crystalline semiconductor matrices to take advantage of their properties and create new structures with new properties for optoelectronic applications. The research team investigates the structure-property relationship of the hybrid structure to gain insight into how the two distinct components interact and what governs the spatial distribution and flow of charge carriers. Building on these insights, the goal is to develop strategies for efficient light-emitting structures in the short-wave infrared spectrum. Additionally, the project trains graduate and undergraduate students and actively engages students from underrepresented groups in STEM, offering research opportunities through the New Haven Promise Program and the Yale STARS Summer Research Program.<br/> <br/>Technical Description<br/><br/>Optical light sources in the short-wave infrared region are essential for bioimaging, medical diagnosis, machine vision, and communication. However, their integration into portable and wearable electronics is currently limited due to the complex fabrication processes required for epitaxially grown semiconductors. This study explores the potential of a novel solution-processed heterostructure—by exploiting QDs as substitutional dopants for bulk crystalline semiconductors—to manipulate the dynamics and transport of energy carriers and thereby modify the electronic and optical properties of the host material. A variety of techniques, including photoemission spectroscopy, pump-probe optical spectroscopy, and synchrotron X-ray scattering, are employed to characterize the judiciously chosen material compositions. The project aims to extend the structural versatility of the hybrid structure, elucidate the mechanisms and efficiency of carrier transfer between localized and delocalized states, and correlate the fundamental physics with the structural properties. This understanding is expected to establish the knowledge base needed for using these materials as both non-coherent and coherent light sources.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

07/08/2024

07/08/2024

None

Grant

47.049

1

4900

4900

2415101

{'FirstName': 'Mengxia', 'LastName': 'Liu', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Mengxia Liu', 'EmailAddress': 'mengxia.liu@yale.edu', 'NSF_ID': '000880896', 'StartDate': '07/08/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Yale University', 'CityName': 'NEW HAVEN', 'ZipCode': '065113572', 'PhoneNumber': '2037854689', 'StreetAddress': '150 MUNSON ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Connecticut', 'StateCode': 'CT', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_ORG': 'CT03', 'ORG_UEI_NUM': 'FL6GV84CKN57', 'ORG_LGL_BUS_NAME': 'YALE UNIV', 'ORG_PRNT_UEI_NUM': 'FL6GV84CKN57'}

{'Name': 'Yale University', 'CityName': 'NEW HAVEN', 'StateCode': 'CT', 'ZipCode': '065160972', 'StreetAddress': '520 West Campus Drive', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Connecticut', 'CountryFlag': '1', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_PERF': 'CT03'}

{'Code': '177500', 'Text': 'ELECTRONIC/PHOTONIC MATERIALS'}

2024~134955

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2415101.xml'}

EAGER: Toward Eco-Friendly Oceanography - Using Biodegradable Materials for Drifting Buoys

NSF

02/01/2024

01/31/2026

{'Value': 'Standard Grant'}

{'Code': '06040100', 'Directorate': {'Abbreviation': 'GEO', 'LongName': 'Directorate For Geosciences'}, 'Division': {'Abbreviation': 'OCE', 'LongName': 'Division Of Ocean Sciences'}}

{'SignBlockName': 'Kandace Binkley', 'PO_EMAI': 'kbinkley@nsf.gov', 'PO_PHON': '7032927577'}

The PIs request funding to investigate the use of bioplastics for oceanography. The proposed biodegradable hull enables a greener way forward for experimental oceanography. It is an important first step toward making buoys with less environmental impact for future networks of small, low power buoys. This women-led team of scientists and engineers strives to create more eco-friendly surface drifting buoys for the Arctic Seas, and the global ocean. It would provide training opportunities for students, enabling them to develop expertise in polymer science and engineering, sustainability, system testing and characterization, and the deployment of buoys. In addition, graduate students involved in the project would participate in the Clean Energy Ambassador Program. This program facilitates their placement in classrooms across the state of Washington, where they will conduct experiments on creating polymer composites from biomass and engage in mentoring interactions with the participating schools. To evaluate the impact of these visits, teachers and hosts will provide feedback through evaluations. The Clean Energy Ambassador Program has established a network of over 500 teachers, ensuring that the outreach activities stemming from this project can be shared with a broad audience of teachers and students. <br/><br/>They propose to investigate the use of bioplastics for oceanography. The field of bioplastics itself is making advances and the biomaterials we intend to use present a cutting-edge approach as such. The PIs would apply this material science focused research in ocean exploration, with the intent to further both the characterization of the material in ocean relevant environments, as well as push the frontier of what is possible in buoy development. A biodegradable hull enables a greener way forward for experimental oceanography. It is an important first step toward making buoys with less environmental impact for future networks of small, low power buoys.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

01/29/2024

01/29/2024

None

Grant

47.050

1

4900

4900

2415106

[{'FirstName': 'Michael', 'LastName': 'Steele', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Michael Steele', 'EmailAddress': 'mas@apl.washington.edu', 'NSF_ID': '000467928', 'StartDate': '01/29/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Anuscheh', 'LastName': 'Nawaz', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Anuscheh Nawaz', 'EmailAddress': 'anuscheh@uw.edu', 'NSF_ID': '000764295', 'StartDate': '01/29/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Eleftheria', 'LastName': 'Roumeli', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Eleftheria Roumeli', 'EmailAddress': 'eroumeli@uw.edu', 'NSF_ID': '000824809', 'StartDate': '01/29/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]

{'Name': 'University of Washington', 'CityName': 'SEATTLE', 'ZipCode': '981951016', 'PhoneNumber': '2065434043', 'StreetAddress': '4333 BROOKLYN AVE NE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Washington', 'StateCode': 'WA', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_ORG': 'WA07', 'ORG_UEI_NUM': 'HD1WMN6945W6', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF WASHINGTON', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'University of Washington', 'CityName': 'SEATTLE', 'StateCode': 'WA', 'ZipCode': '981951016', 'StreetAddress': '4333 BROOKLYN AVE NE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Washington', 'CountryFlag': '1', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_PERF': 'WA07'}

{'Code': '168000', 'Text': 'OCEAN TECH & INTERDISC COORDIN'}

2024~299998

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2415106.xml'}

CAREER: First-principles Predictive Understanding of Chemical Order in Complex Concentrated Alloys: Structures, Dynamics, and Defect Characteristics

NSF

03/15/2024

04/30/2025

{'Value': 'Continuing Grant'}

{'Code': '03070000', 'Directorate': {'Abbreviation': 'MPS', 'LongName': 'Direct For Mathematical & Physical Scien'}, 'Division': {'Abbreviation': 'DMR', 'LongName': 'Division Of Materials Research'}}

{'SignBlockName': 'Serdar Ogut', 'PO_EMAI': 'sogut@nsf.gov', 'PO_PHON': '7032924429'}

NONTECHNICAL SUMMARY<br/><br/>This CAREER award supports research and educational activities to develop quantum mechanical and machine learning methods to understand and design complex multi-element alloys at the atomic level. The project focuses on complex concentrated alloys (CCAs), a class of novel alloys that mix atoms of different species at nearly equal ratios. The scientific drive for studying CCAs is to understand and utilize the vast chemical and structural design space associated with multiple elements in search of new materials properties. Current understanding about the stability, structures, and properties of alloys is limited to the corners and edges of the multi-element space, such as binary or dilute alloys. The information for CCAs close to the center of the composition space is virtually non-existent for systems with four or more elements. The project intends to fill this knowledge gap in alloy theory for these complex alloy systems by (i) establishing an accurate predictive understanding of the atomic structures in CCAs through a combination of quantum mechanical calculations and statistical mechanics methods, and (ii) integrating quantum mechanical calculations, empirical models and close-loop machine learning methods to predict the structural and defect features in CCAs for accelerated design of CCAs for structural or functional applications. The multidisciplinary nature of the project brings perspectives from multiple academic fields into the forefront of materials research. The focus of the technologically relevant CCAs will strengthen the U.S. leadership in fundamental alloy research. <br/><br/>The education and outreach activities of the project includes five integrated parts that address learning tool innovation, broadening participation, youth material education, summer research exposure, and research career development. The project brings together national and local partners to create a multidisciplinary team with complementary expertise to strengthen Science, Technology, Engineering, and Mathematics education and raise the awareness of materials science. In collaboration with Amazon, a cloud-based learning app will be developed to transplant the PI’s research and introduce materials and data science to the general public. The PI will collaborate with SMASH Illinois to offer academic and social programs to underrepresented students to broaden participation in materials education. In parallel, summer camps with North Central College and Questek, as well as high school research programs with Adlai E. Stevenson High School will be expanded to expose the younger generation to materials science. The PI will also work closely with undergraduate and graduate students to foster multidisciplinary career development via project-based research programs.<br/><br/>TECHNICAL SUMMARY<br/><br/>This CAREER award supports research and educational activities to develop first-principles and data-driven methods to understand the atomic nature of short range order (SRO) in complex concentrated alloys (CCAs) and how such chemical order influences lattice distortion, dynamics, and defect structures, thus creating opportunities for designing new advanced alloys. Severe lattice distortion is an important phenomenon that is correlated to a variety of physical and chemical properties in CCAs. However, the nature of severe lattice distortions in CCAs is poorly understood, especially with the coupling of SRO. The PI will study SRO and related lattice distortions in CCAs with a unique synergy of mechanism investigation, predictive modeling, and methodology development. The research will elucidate SRO on the structures of lattice distortions in CCAs, which will be utilized to quantify the impact of the distorted lattices on the phonon characteristics of CCAs. Results and methodology from bulk CCAs will be applied to establish a predictive mapping linking defect characteristics with local environments in CCAs, providing the foundation for computational design of CCAs for superior mechanical properties. The project will be driven by the parallel research on a hierarchical data-driven computational framework that enables efficient predictions of structure-property relationships for CCAs. <br/><br/>The education and outreach activities of the project includes five integrated parts that address learning tool innovation, broadening participation, youth material education, summer research exposure, and research career development. The project brings together national and local partners to create a multidisciplinary team with complementary expertise to strengthen Science, Technology, Engineering, and Mathematics education and raise the awareness of materials science. In collaboration with Amazon, a cloud-based learning app will be developed to transplant the PI’s research and introduce materials and data science to the general public. The PI will collaborate with SMASH Illinois to offer academic and social programs to underrepresented students to broaden participation in materials education. In parallel, summer camps with North Central College and Questek, as well as high school research programs with Adlai E. Stevenson High School will be expanded to expose the younger generation to materials science. The PI will also work closely with undergraduate and graduate students to foster multidisciplinary career development via project-based research programs.<br/><br/>This award is jointly supported by the Division of Materials Research and the NSF Office of Advanced Cyberinfrastructure.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

03/08/2024

06/03/2024

None

Grant

47.049, 47.070

1

4900

4900

2415119

{'FirstName': 'Wei', 'LastName': 'Chen', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Wei Chen', 'EmailAddress': 'wchen226@buffalo.edu', 'NSF_ID': '000705021', 'StartDate': '03/08/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'SUNY at Buffalo', 'CityName': 'AMHERST', 'ZipCode': '142282577', 'PhoneNumber': '7166452634', 'StreetAddress': '520 LEE ENTRANCE STE 211', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'New York', 'StateCode': 'NY', 'CONGRESSDISTRICT': '26', 'CONGRESS_DISTRICT_ORG': 'NY26', 'ORG_UEI_NUM': 'LMCJKRFW5R81', 'ORG_LGL_BUS_NAME': 'RESEARCH FOUNDATION FOR THE STATE UNIVERSITY OF NEW YORK, THE', 'ORG_PRNT_UEI_NUM': 'GMZUKXFDJMA9'}

{'Name': 'SUNY at Buffalo', 'CityName': 'AMHERST', 'StateCode': 'NY', 'ZipCode': '142282577', 'StreetAddress': '520 LEE ENTRANCE STE 211', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'New York', 'CountryFlag': '1', 'CONGRESSDISTRICT': '26', 'CONGRESS_DISTRICT_PERF': 'NY26'}

[{'Code': '176500', 'Text': 'CONDENSED MATTER & MAT THEORY'}, {'Code': '689200', 'Text': 'CI REUSE'}]

['2020~114324', '2022~102216', '2023~100293', '2024~100403']

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2415119.xml'}

I-Corps: Translation Potential of a Disaster Management Enterprise Information Resource Planning System for Disaster Response

NSF

05/01/2024

04/30/2025

{'Value': 'Standard Grant'}

{'Code': '15030000', 'Directorate': {'Abbreviation': 'TIP', 'LongName': 'Dir for Tech, Innovation, & Partnerships'}, 'Division': {'Abbreviation': 'TI', 'LongName': 'Translational Impacts'}}

{'SignBlockName': 'Molly Wasko', 'PO_EMAI': 'mwasko@nsf.gov', 'PO_PHON': '7032924749'}

The broader impact of this I-Corps project is based on the development of a disaster management enterprise information resource planning system, an advanced technological solution designed to rapidly implement emergency responses. This capability equips emergency responders with immediate, actionable intelligence, which facilitates swift decision-making and effective resource allocation in emergency situations. The potential advantages of this system include significantly enhancing the efficiency and accuracy of emergency management processes by quickly identifying and categorizing urgent needs under different disaster conditions. Overall, the broad applicability this technology is aimed at improving survival rates, reducing the overall impact of disasters, and contributing to societal well-being. By pushing the boundaries of current emergency management technologies, this system could enhance emergency preparedness, response, and recovery efforts, making a notable advancement in crisis management and public safety.<br/><br/>This I-Corps project utilizes experiential learning coupled with a first-hand investigation of the industry ecosystem to assess the translation potential of the technology. The solution is based on the development of a disaster management enterprise information resource planning system which employs state-of-the-art deep learning techniques to facilitate the real-time processing and classification of extensive data streams, thereby offering a critical advancement in emergency management technology. This approach focuses on data classification and analysis to efficiently identify urgent needs and prioritize critical information, facilitating rapid decision-making in crisis situations. The system's novel innovation lies in its phrase extraction methods, context-aware features, and sophisticated data categorization techniques, which ensure high accuracy and relevancy in dynamically-changing disaster scenarios. These features highlight the system's potential to significantly improve the speed and precision of emergency responses. Furthermore, the system’s capacity for continuous learning and adaptation allows it to become increasingly effective over time, enabling the provision of faster, tailored emergency response strategies.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

04/22/2024

04/22/2024

None

Grant

47.084

1

4900

4900

2415132

{'FirstName': 'Sanjay', 'LastName': 'Madria', 'PI_MID_INIT': 'k', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Sanjay k Madria', 'EmailAddress': 'madrias@mst.edu', 'NSF_ID': '000289664', 'StartDate': '04/22/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Missouri University of Science and Technology', 'CityName': 'ROLLA', 'ZipCode': '654091330', 'PhoneNumber': '5733414134', 'StreetAddress': '300 W. 12TH STREET', 'StreetAddress2': '202 CENTENNIAL HALL', 'CountryName': 'United States', 'StateName': 'Missouri', 'StateCode': 'MO', 'CONGRESSDISTRICT': '08', 'CONGRESS_DISTRICT_ORG': 'MO08', 'ORG_UEI_NUM': 'Y6MGH342N169', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF MISSOURI SYSTEM', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Missouri University of Science and Technology', 'CityName': 'ROLLA', 'StateCode': 'MO', 'ZipCode': '654091330', 'StreetAddress': '300 W. 12TH STREET', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Missouri', 'CountryFlag': '1', 'CONGRESSDISTRICT': '08', 'CONGRESS_DISTRICT_PERF': 'MO08'}

{'Code': '802300', 'Text': 'I-Corps'}

2024~50000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2415132.xml'}

The effect of interlocutor distance in the grammars of bilingual communities

NSF

08/01/2024

07/31/2027

{'Value': 'Standard Grant'}

{'Code': '04040000', 'Directorate': {'Abbreviation': 'SBE', 'LongName': 'Direct For Social, Behav & Economic Scie'}, 'Division': {'Abbreviation': 'BCS', 'LongName': 'Division Of Behavioral and Cognitive Sci'}}

{'SignBlockName': 'Jorge Valdes Kroff', 'PO_EMAI': 'jvaldesk@nsf.gov', 'PO_PHON': '7032927920'}

Linguistic research seeks to uncover language universals-properties that characterize all human languages-as well as the reasons why languages differ. Across languages, demonstratives like "this/that" in English and "este/ese/aquel" in Spanish provide an excellent tool for advancing these aims because demonstratives exist in all languages and are used to manage attention, which is a general function of language. For example, when a speaker says "this book is heavy," the use of "this" draws attention to a particular book. At the same time, demonstratives vary across languages in number and meaning. This project focuses on one way that demonstratives are different across languages: addressee effects. When a speaker says something like "look at this book" or "look at that book," does she only focus on herself and the book when choosing to say this or that (e.g., this = near me, that = far from me)? Or does the person she’s talking to-her addressee-affect this choice? On possibility is that demonstrative usage is affected by how close the addressee is to the referent and whether the speaker and addressee are paying attention to the same referent. Given that demonstratives manage attention, addressee effects should be present in all languages. Yet previous research has found that this is not the case. These unexpected differences require greater examination. With this aim, this project investigates demonstrative use in three bilingual communities. The languages under study vary in the number of demonstratives that they use. Because of this wide variation, comparing across the languages advances scientific understanding of how inventory size-the number of demonstrative terms in a system-shapes demonstrative use. <br/><br/>Participants complete a language dominance assessment and two experiments, one manipulating addressee location and the other addressee attention. Bilinguals complete the experiments in both their languages. Addressee location effects are predicted to occur mainly in languages with larger demonstrative inventories. In contrast, addressee attention effects may be more universal. Besides testing these predictions, the project's focus on bilingualism informs key understanding of how bilinguals' languages interact. For example, if addressee effects have been identified in one language but not the other, what happens among bilingual speakers? The three communities offer a unique testing ground for studying bilingualism because they represent distinct bilingual profiles. Comparing across different communities illuminates how language dominance predicts language interaction. The project also contributes to methodologies for studying bilingualism worldwide and serves as an intensive research training experience for students at the University of New Mexico, a minority and Hispanic serving institution. Finally, the project benefits communities by building capacity via workshops, language materials designed for educators, and by widely disseminating articles in newsletters that translate the research findings for the community at large.<br/><br/>This project is jointly funded by the Linguistics Program and the Established Program to Stimulate Competitive Research (EPSCoR).<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

07/25/2024

07/25/2024

None

Grant

47.075, 47.083

1

4900

4900

2415153

[{'FirstName': 'Rosa', 'LastName': 'Vallejos Yopan', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Rosa Vallejos Yopan', 'EmailAddress': 'rvallejos@unm.edu', 'NSF_ID': '000435697', 'StartDate': '07/25/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Naomi', 'LastName': 'Shin', 'PI_MID_INIT': 'L', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Naomi L Shin', 'EmailAddress': 'naomishin@unm.edu', 'NSF_ID': '000962137', 'StartDate': '07/25/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}]

{'Name': 'University of New Mexico', 'CityName': 'ALBUQUERQUE', 'ZipCode': '87131', 'PhoneNumber': '5052774186', 'StreetAddress': '1700 LOMAS BLVD NE STE 2200', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'New Mexico', 'StateCode': 'NM', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_ORG': 'NM01', 'ORG_UEI_NUM': 'F6XLTRUQJEN4', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF NEW MEXICO', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'University of New Mexico', 'CityName': 'ALBUQUERQUE', 'StateCode': 'NM', 'ZipCode': '871063837', 'StreetAddress': '1700 LOMAS BLVD NE STE 2200', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'New Mexico', 'CountryFlag': '1', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_PERF': 'NM01'}

[{'Code': '131100', 'Text': 'Linguistics'}, {'Code': '915000', 'Text': 'EPSCoR Co-Funding'}]

2024~494659

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2415153.xml'}

Travel: Student Travel Support for the International Conference on Data Engineering (ICDE) 2024

NSF

03/01/2024

08/31/2024

{'Value': 'Standard Grant'}

{'Code': '05020000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'IIS', 'LongName': 'Div Of Information & Intelligent Systems'}}

{'SignBlockName': 'Judith Cushing', 'PO_EMAI': 'jcushing@nsf.gov', 'PO_PHON': '3607016450'}

This proposal seeks a travel grant to enable students in US universities to participate in the IEEE International Conference on Data Engineering (ICDE 2024), which will be held in Utrecht, Netherlands, May 13-16, 2024. The grant will be used exclusively for students in US-based institutions, and it will enable the supported students to travel to Utrecht, Netherlands to participate in the conference and its associated workshops. The funding will defray the registration, travel, and lodging costs for the students. <br/><br/>It will enable a life-enriching first-time experience for many students, giving them a taste of the research environment in both academic and industrial circles worldwide. ICDE is a premier conference in the area of databases, and participation in this conference will enable the students to enhance their scientific foundation and build their professional networks.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

02/29/2024

02/29/2024

None

Grant

47.070

1

4900

4900

2415174

[{'FirstName': 'Gautam', 'LastName': 'Das', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Gautam Das', 'EmailAddress': 'gdas@cse.uta.edu', 'NSF_ID': '000341181', 'StartDate': '02/29/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Ashraf', 'LastName': 'Aboulnaga', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Ashraf Aboulnaga', 'EmailAddress': 'ashraf.aboulnaga@uta.edu', 'NSF_ID': '000986439', 'StartDate': '02/29/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}]

{'Name': 'University of Texas at Arlington', 'CityName': 'ARLINGTON', 'ZipCode': '760199800', 'PhoneNumber': '8172722105', 'StreetAddress': '701 S NEDDERMAN DR', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Texas', 'StateCode': 'TX', 'CONGRESSDISTRICT': '25', 'CONGRESS_DISTRICT_ORG': 'TX25', 'ORG_UEI_NUM': 'LMLUKUPJJ9N3', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF TEXAS AT ARLINGTON', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'University of Texas at Arlington', 'CityName': 'ARLINGTON', 'StateCode': 'TX', 'ZipCode': '760199800', 'StreetAddress': '701 S. NEDDERMAN DR', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Texas', 'CountryFlag': '1', 'CONGRESSDISTRICT': '25', 'CONGRESS_DISTRICT_PERF': 'TX25'}

{'Code': '736400', 'Text': 'Info Integration & Informatics'}

2024~25000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2415174.xml'}

University of Washington – R/V Thomas G. Thompson and R/V Rachel Carson Shipboard Scientific Support Equipment (SSSE) 2024

NSF

06/01/2024

05/31/2026

{'Value': 'Standard Grant'}

{'Code': '06040100', 'Directorate': {'Abbreviation': 'GEO', 'LongName': 'Directorate For Geosciences'}, 'Division': {'Abbreviation': 'OCE', 'LongName': 'Division Of Ocean Sciences'}}

{'SignBlockName': 'George Voulgaris', 'PO_EMAI': 'gvoulgar@nsf.gov', 'PO_PHON': '7032927399'}

This award provides support for Shipboard Scientific Support Equipment (SSSE) for R/V Thomas G. Thompson, a 274-foot general-purpose, global research vessel, and R/V Rachel Carson, a 72-foot coastal research vessel. Both vessels are operated by the University of Washington as part of the U.S. Academic Research Fleet. This award will enable the acquisition of Keyboard-Video-Monitor (KVM) system controls for both the R/V Thompson and R/V Carson and multiple video monitors for R/V Thompson's computer lab for science and shipboard data systems. KVM systems have become standard on global class vessels in the fleet and valuable for situational awareness on any research vessel. R/V Thompson currently has an IP-based CCTV system that was an item flagged for replacement during a recent ship inspection and will be replaced with an up-to-date reliable system with this request. Finally, CTD operations on R/V Thompson will be improved by acquiring a sled on a track to replace the current accordion system to stage the ship's CTD package. The new system will allow deployment in much higher sea states with a greater margin of safety.<br/><br/>The principal impact of the present proposal is under Merit Review Criterion 2 of the Proposal Guidelines (NSF 23-525). It provides infrastructure support for scientists to use the vessel and its shared-use instrumentation in support of their NSF-funded oceanographic research projects (which individually undergo separate review by the relevant research program of NSF). The acquisition, maintenance, and operation of shared-use instrumentation allows NSF-funded researchers from any US university or other organization access to well-maintained, high-quality, calibrated instruments for their research. It ensures the collection of high-quality oceanographic data in support of science, reduces the cost of that research, and expands the base of potential researchers.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

05/30/2024

05/30/2024

None

Grant

47.050

1

4900

4900

2415177

{'FirstName': 'Robert', 'LastName': 'Kamphaus', 'PI_MID_INIT': 'A', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Robert A Kamphaus', 'EmailAddress': 'kamphaus@uw.edu', 'NSF_ID': '000800132', 'StartDate': '05/30/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'University of Washington', 'CityName': 'SEATTLE', 'ZipCode': '981951016', 'PhoneNumber': '2065434043', 'StreetAddress': '4333 BROOKLYN AVE NE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Washington', 'StateCode': 'WA', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_ORG': 'WA07', 'ORG_UEI_NUM': 'HD1WMN6945W6', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF WASHINGTON', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'University of Washington', 'CityName': 'SEATTLE', 'StateCode': 'WA', 'ZipCode': '981951016', 'StreetAddress': '4333 BROOKLYN AVE NE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Washington', 'CountryFlag': '1', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_PERF': 'WA07'}

{'Code': '541600', 'Text': 'SHIPBOARD SCIENTIFIC SUPP EQUI'}

2024~158500

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2415177.xml'}

NSF-MeitY: Metal Additive Manufacturing, Advanced Photon Source, In-Situ Monitoring, Rare-Earth Magnet, Materials Design

NSF

08/15/2024

07/31/2027

{'Value': 'Standard Grant'}

{'Code': '07030000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'CMMI', 'LongName': 'Div Of Civil, Mechanical, & Manufact Inn'}}

{'SignBlockName': 'Satish Bukkapatnam', 'PO_EMAI': 'sbukkapa@nsf.gov', 'PO_PHON': '7032924813'}

With more than half of the US electricity consumption due to electrical motors, even small gains in efficiency, especially of the emerging direct current (DC) motors, would have a profound impact on energy usage. Permanent magnets are the most essential component in DC motors, and rare earth permanent magnets are far superior to any other permanent magnet. But since supply chain issues beset rare earth materials, more efficient use of these natural resources is paramount. Additive manufacturing (AM) offers the ability to produce near-net-shape and net-shape parts, significantly decreasing waste of these materials. Additionally, AM provides unique design strategies which can revolutionize motor design, further enhancing performance. More pertinently, AM processes for magnetic materials have not received much attention. This NSF-MeitY award is an international collaboration with the Ministry of Electronics and Information Technology of India (MeitY). It supports research that seeks to understand crucial phenomena, namely, the material solidification and development of microstructure in the AM process for rare earth permanent magnets, which critically affect the magnetic performance.<br/> <br/>This project will achieve a comprehensive understanding of the additive manufacturing (AM) of rare earth permanent magnets through three main objectives: (1) designing alloys tailored for the solidification conditions encountered during AM; (2) conducting in situ studies of the AM process to gain insights into the processing science of complex alloy systems; and (3) fabricating part-level magnets using commercial laser powder bed fusion machines, producing both isotropic and anisotropic grain structures, from the knowledge gained in Objectives 1 and 2. The results of the project will lead to a thorough understanding of the thermokinetics of the AM process, and from that detailed processing maps to enable exact microstructural design during AM. This project will involve student and faculty exchanges between the University of Nebraska-Lincoln and the India Institute of Technology-Kharagpur, and train students in magnetic materials and AM to ensure continued US leadership in these areas.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/05/2024

08/05/2024

None

Grant

47.041

1

4900

4900

2415193

[{'FirstName': 'Jeffrey', 'LastName': 'Shield', 'PI_MID_INIT': 'E', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Jeffrey E Shield', 'EmailAddress': 'jshield2@unl.edu', 'NSF_ID': '000405480', 'StartDate': '08/05/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Qilin', 'LastName': 'Guo', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Qilin Guo', 'EmailAddress': 'qilin.guo@unl.edu', 'NSF_ID': '000937333', 'StartDate': '08/05/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]

{'Name': 'University of Nebraska-Lincoln', 'CityName': 'LINCOLN', 'ZipCode': '685032427', 'PhoneNumber': '4024723171', 'StreetAddress': '2200 VINE ST # 830861', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Nebraska', 'StateCode': 'NE', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_ORG': 'NE01', 'ORG_UEI_NUM': 'HTQ6K6NJFHA6', 'ORG_LGL_BUS_NAME': 'BOARD OF REGENTS OF THE UNIVERSITY OF NEBRASKA', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'University of Nebraska-Lincoln', 'CityName': 'LINCOLN', 'StateCode': 'NE', 'ZipCode': '685032427', 'StreetAddress': '2200 VINE ST', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Nebraska', 'CountryFlag': '1', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_PERF': 'NE01'}

[{'Code': '088Y00', 'Text': 'AM-Advanced Manufacturing'}, {'Code': '138500', 'Text': 'SSA-Special Studies & Analysis'}]

2024~619688

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2415193.xml'}

Developing a Measure of Diverse Student Perceptions and Valuation of Flipped Instruction in Chemistry

NSF

10/01/2024

09/30/2027

{'Value': 'Standard Grant'}

{'Code': '11040000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DUE', 'LongName': 'Division Of Undergraduate Education'}}

{'SignBlockName': 'Kalyn Owens', 'PO_EMAI': 'kowens@nsf.gov', 'PO_PHON': '7032924615'}

This project aims to serve the national interest by establishing and measuring student perceptions of fundamental design principles of effective and inclusive flipped undergraduate gateway chemistry courses. Flipped instruction is a popular evidence-based instructional practice among chemistry faculty in the United States. It enables in-class facilitation of active student engagement with chemical concepts. Despite its popularity, historically marginalized student groups may benefit the least, if at all, from flipped undergraduate gateway chemistry courses. This project proposes to advance understanding of these achievement differences by examining how diverse students engage in these courses. The project intends to advance theses aims through developing a conceptual framework of essential design principles of effective and inclusive flipped undergraduate gateway chemistry courses and a related measurement tool for use by faculty. The conceptual framework is intentionally grounded in students’ diverse backgrounds and how they engage with, perceive, and value flipped instruction in undergraduate gateway chemistry courses. Importantly, the framework has the potential to open a productive pipeline of evidence leading to future identification, manipulation, adoption, and amplification of high impact flipped instruction for diverse groups in undergraduate gateway chemistry courses.<br/><br/>The project plans to use a sequential exploratory mixed methods study design to develop the conceptual framework and a corresponding psychometric instrument to measure diverse students’ perceptions and valuation of the essential design principles. The project’s development process is designed to begin with in-depth interviews with students from flipped General and Organic Chemistry courses taught by 6 field-leading instructors at public, private, research intensive, and teaching institutions across 5 states. The process continues by generating a set of essential design principles from interview data which will be used to develop items for the psychometric instrument. The project then intends to refine and test the instrument by returning to new cohorts of students at the same institutions in its final two years. To ensure STEM diversity enhancement, historically marginalized student groups will be proactively included in every project phase. This project also plans to provide training for instructors and researchers to adopt the flipped instruction essential design principles with fidelity in their local undergraduate gateway chemistry courses. The NSF IUSE: EDU Program supports research and development projects to improve the effectiveness of STEM education for all students. Through the Engaged Student Learning track, the program supports the creation, exploration, and implementation of promising practices and tools.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/22/2024

08/22/2024

None

Grant

47.076

1

4900

4900

2415197

[{'FirstName': 'Senetta', 'LastName': 'Bancroft', 'PI_MID_INIT': 'F', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Senetta F Bancroft', 'EmailAddress': 'senetta.bancroft@siu.edu', 'NSF_ID': '000730715', 'StartDate': '08/22/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Heidi', 'LastName': 'Bacon', 'PI_MID_INIT': 'R', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Heidi R Bacon', 'EmailAddress': 'hrbacon@siu.edu', 'NSF_ID': '000804321', 'StartDate': '08/22/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Jennifer', 'LastName': 'Koran', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Jennifer Koran', 'EmailAddress': 'jkoran@siu.edu', 'NSF_ID': '000882111', 'StartDate': '08/22/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]

{'Name': 'Southern Illinois University at Carbondale', 'CityName': 'CARBONDALE', 'ZipCode': '629014302', 'PhoneNumber': '6184534540', 'StreetAddress': '900 S NORMAL AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Illinois', 'StateCode': 'IL', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_ORG': 'IL12', 'ORG_UEI_NUM': 'Y28BEBJ4MNU7', 'ORG_LGL_BUS_NAME': 'BOARD OF TRUSTEES OF SOUTHERN ILLINOIS UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Southern Illinois University Carbondale', 'CityName': 'CARBONDALE', 'StateCode': 'IL', 'ZipCode': '629014302', 'StreetAddress': 'Wham Education Building; Room Number 327', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Illinois', 'CountryFlag': '1', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_PERF': 'IL12'}

{'Code': '199800', 'Text': 'IUSE'}

2024~399853

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2415197.xml'}

Collaborative Research: NSF-MeitY: CSR: Small: Eco-LLM: Energy-Efficient Computation and Communication for Large Language Models with CXL-based Chip Architecture and Software

NSF

10/01/2024

09/30/2027

{'Value': 'Standard Grant'}

{'Code': '05050000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CNS', 'LongName': 'Division Of Computer and Network Systems'}}

{'SignBlockName': 'Daniela Oliveira', 'PO_EMAI': 'doliveir@nsf.gov', 'PO_PHON': '7032920000'}

Although crucial for advanced Artificial Intelligence (AI) applications due to their language understanding and generation capabilities, Large Language Models (LLMs) are energy intensive. This project’s goals and novelty are to enhance the efficiency of training and inference associated with LLMs by leveraging emerging high-speed networks and computing architecture. The project’s broader significance and importance are to (1) enable a broad range of LLMs to efficiently operate, advancing AI applications at a low energy cost; (2) strengthen international research collaboration between U.S. and India researchers; and (3) provide educational opportunities for graduate students.<br/><br/>This project addresses the energy efficiency challenges of LLMs by optimizing their energy consumption in heterogeneous Compute Express Link (CXL)-enabled hardware environments. By leveraging High-Performance Computing (HPC) middleware and the high-bandwidth, low-latency features of CXL, the project aims to ensure sustainable and efficient AI operations. This project seeks to find solutions to the following set of fundamental issues in training and using LLMs at scale: 1) identifying and characterizing idleness in the LLM workloads; 2) using the knowledge of long idleness to insert low-overhead Dynamic Voltage and Frequency Scaling (DVFS) control and undervolting to save static energy consumption; 3) designing CXL-aware and energy-efficient Message Passing Interface (MPI)-based communication runtime for LLM training and inferencing; and 4) studying the overall impact of the integrated systems on the energy consumption of LLM training and inference. The results are disseminated to collaborating organizations to impact their HPC/AI software applications and hardware chip designs, promoting broader societal advancement through improved technological capabilities.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/26/2024

08/26/2024

None

Grant

47.070, 47.079

1

4900

4900

2415201

[{'FirstName': 'Dhabaleswar', 'LastName': 'Panda', 'PI_MID_INIT': 'K', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Dhabaleswar K Panda', 'EmailAddress': 'panda@cse.ohio-state.edu', 'NSF_ID': '000487085', 'StartDate': '08/26/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Hari', 'LastName': 'Subramoni', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Hari Subramoni', 'EmailAddress': 'subramoni.1@osu.edu', 'NSF_ID': '000704577', 'StartDate': '08/26/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Aamir', 'LastName': 'Shafi', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Aamir Shafi', 'EmailAddress': 'shafi.16@osu.edu', 'NSF_ID': '000841500', 'StartDate': '08/26/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Mustafa', 'LastName': 'Abduljabbar', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Mustafa Abduljabbar', 'EmailAddress': 'abduljabbar.1@osu.edu', 'NSF_ID': '000931934', 'StartDate': '08/26/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]

{'Name': 'Ohio State University', 'CityName': 'COLUMBUS', 'ZipCode': '432101016', 'PhoneNumber': '6146888735', 'StreetAddress': '1960 KENNY RD', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Ohio', 'StateCode': 'OH', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_ORG': 'OH03', 'ORG_UEI_NUM': 'DLWBSLWAJWR1', 'ORG_LGL_BUS_NAME': 'OHIO STATE UNIVERSITY, THE', 'ORG_PRNT_UEI_NUM': 'MN4MDDMN8529'}

{'Name': 'Ohio State University', 'CityName': 'COLUMBUS', 'StateCode': 'OH', 'ZipCode': '432101016', 'StreetAddress': '1960 KENNY RD', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Ohio', 'CountryFlag': '1', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_PERF': 'OH03'}

[{'Code': '054Y00', 'Text': 'GVF - Global Venture Fund'}, {'Code': '735400', 'Text': 'CSR-Computer Systems Research'}]

2024~400000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2415201.xml'}

Collaborative Research: NSF-MeitY: CSR: Small: Eco-LLM: Energy-Efficient Computation and Communication for Large Language Models with CXL-based Chip Architecture and Software

NSF

10/01/2024

09/30/2027

{'Value': 'Standard Grant'}

{'Code': '05050000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CNS', 'LongName': 'Division Of Computer and Network Systems'}}

{'SignBlockName': 'Daniela Oliveira', 'PO_EMAI': 'doliveir@nsf.gov', 'PO_PHON': '7032920000'}

Although crucial for advanced Artificial Intelligence (AI) applications due to their language understanding and generation capabilities, Large Language Models (LLMs) are energy intensive. This project’s goals and novelty are to enhance the efficiency of training and inference associated with LLMs by leveraging emerging high-speed networks and computing architecture. The project’s broader significance and importance are to (1) enable a broad range of LLMs to efficiently operate, advancing AI applications at a low energy cost; (2) strengthen international research collaboration between U.S. and India researchers; and (3) provide educational opportunities for graduate students.<br/><br/>This project addresses the energy efficiency challenges of LLMs by optimizing their energy consumption in heterogeneous Compute Express Link (CXL)-enabled hardware environments. By leveraging High-Performance Computing (HPC) middleware and the high-bandwidth, low-latency features of CXL, the project aims to ensure sustainable and efficient AI operations. This project seeks to find solutions to the following set of fundamental issues in training and using LLMs at scale: 1) identifying and characterizing idleness in the LLM workloads; 2) using the knowledge of long idleness to insert low-overhead Dynamic Voltage and Frequency Scaling (DVFS) control and undervolting to save static energy consumption; 3) designing CXL-aware and energy-efficient Message Passing Interface (MPI)-based communication runtime for LLM training and inferencing; and 4) studying the overall impact of the integrated systems on the energy consumption of LLM training and inference. The results are disseminated to collaborating organizations to impact their HPC/AI software applications and hardware chip designs, promoting broader societal advancement through improved technological capabilities.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/26/2024

08/26/2024

None

Grant

47.070

1

4900

4900

2415202

{'FirstName': 'Laxmi', 'LastName': 'Bhuyan', 'PI_MID_INIT': 'N', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Laxmi N Bhuyan', 'EmailAddress': 'bhuyan@cs.ucr.edu', 'NSF_ID': '000318919', 'StartDate': '08/26/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'University of California-Riverside', 'CityName': 'RIVERSIDE', 'ZipCode': '925210001', 'PhoneNumber': '9518275535', 'StreetAddress': '200 UNIVERSTY OFC BUILDING', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'California', 'StateCode': 'CA', 'CONGRESSDISTRICT': '39', 'CONGRESS_DISTRICT_ORG': 'CA39', 'ORG_UEI_NUM': 'MR5QC5FCAVH5', 'ORG_LGL_BUS_NAME': 'REGENTS OF THE UNIVERSITY OF CALIFORNIA AT RIVERSIDE', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'University of California-Riverside', 'CityName': 'RIVERSIDE', 'StateCode': 'CA', 'ZipCode': '925210001', 'StreetAddress': '200 UNIVERSTY OFC BUILDING', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'California', 'CountryFlag': '1', 'CONGRESSDISTRICT': '39', 'CONGRESS_DISTRICT_PERF': 'CA39'}

{'Code': '735400', 'Text': 'CSR-Computer Systems Research'}

2024~200000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2415202.xml'}

Developing new methodologies to identify organic primate tools

NSF

10/15/2024

09/30/2027

{'Value': 'Standard Grant'}

{'Code': '04040000', 'Directorate': {'Abbreviation': 'SBE', 'LongName': 'Direct For Social, Behav & Economic Scie'}, 'Division': {'Abbreviation': 'BCS', 'LongName': 'Division Of Behavioral and Cognitive Sci'}}

{'SignBlockName': 'Marta Alfonso-Durruty', 'PO_EMAI': 'malfonso@nsf.gov', 'PO_PHON': '7032927811'}

Human adaptability is highly dependent on technology. However, the current knowledge of early technological development derives almost exclusively from stone tools and fossil bones found in the archaeological record. Tools made from organic materials (i.e., wood) are intrinsically perishable and as such are almost entirely absent in the early record of human material culture, leading to an incomplete picture of human technology's origins. This study investigates non-human primate species that use wooden tools as an analogue for the possible behavioral diversity of ancient human ancestors. Organic tools used by non-human primates, are analyzed to identify the resulting modifications. These changes are compared with those observed in wood that was naturally altered. The research employs novel technologies such as machine learning and experiments with robots to identify and standardize diagnostic modifications in ancient fossil wood that show similar damage patterns found in modern primate tools. The resulting methods are applied to fossilized wood remains dated to 4-2 million years ago to investigate wooden tool use in early human ancestors. <br/><br/>The goal of this study is two-fold: (1) to develop a method to identify evidence of percussive tool use in wood (organic tools), and (2) to establish whether there is evidence of percussive organic tool use in fossil wood remains dated between 4.0-2.0 Mya. To attain these goals, researchers collect, document, and analyze organic tools used by non-human primates. Additionally, controlled experiments with a percussive robot are carried out to investigate the effect of various variables (e.g., species, moisture content, etc.) on the formation of percussive traces on wood. Researchers document a variety of natural damage patterns (e.g., due to fungus or insect activity, or due to taphonomic processes). The information is analyzed to create a catalogue of natural and artificial damage patterns. Machine learning models analyze these patterns, distinguishing between natural and tool-use induced damage. Researchers then collect and document fossil wood specimens. Their antiquity is stablished by dating thin sectioned fossil wood (uranium/lead dating), as well as the associated strata (paleomagnetic and tephrochronology analyses). The damage catalog and the AI models are applied to identify patterns of percussive use in the fossilized wood. The study offers new insights into early human behavior and the origins of human technology.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/08/2024

08/08/2024

None

Grant

47.075

1

4900

4900

2415207

[{'FirstName': 'Chen', 'LastName': 'Zeng', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Chen Zeng', 'EmailAddress': 'chenz@gwu.edu', 'NSF_ID': '000162089', 'StartDate': '08/08/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'David', 'LastName': 'Braun', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'David Braun', 'EmailAddress': 'drbraun76@gmail.com', 'NSF_ID': '000191875', 'StartDate': '08/08/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Lydia', 'LastName': 'Luncz', 'PI_MID_INIT': 'V', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Lydia V Luncz', 'EmailAddress': 'lydialuncz@gwu.edu', 'NSF_ID': '000919101', 'StartDate': '08/08/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]

{'Name': 'George Washington University', 'CityName': 'WASHINGTON', 'ZipCode': '200520042', 'PhoneNumber': '2029940728', 'StreetAddress': '1918 F ST NW', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'District of Columbia', 'StateCode': 'DC', 'CONGRESSDISTRICT': '00', 'CONGRESS_DISTRICT_ORG': 'DC00', 'ORG_UEI_NUM': 'ECR5E2LU5BL6', 'ORG_LGL_BUS_NAME': 'GEORGE WASHINGTON UNIVERSITY (THE)', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'George Washington University', 'CityName': 'WASHINGTON', 'StateCode': 'DC', 'ZipCode': '200520042', 'StreetAddress': '1918 F ST NW', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'District of Columbia', 'CountryFlag': '1', 'CONGRESSDISTRICT': '00', 'CONGRESS_DISTRICT_PERF': 'DC00'}

{'Code': '139100', 'Text': 'Archaeology'}

2024~317985

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2415207.xml'}

Collaborative Research: NSF-MeitY: CNS Core: Small: Learning-Assisted Integrated Sensing, Communication and Security for 6G UAV Networks

NSF

10/01/2024

09/30/2027

{'Value': 'Standard Grant'}

{'Code': '05050000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CNS', 'LongName': 'Division Of Computer and Network Systems'}}

{'SignBlockName': 'Alhussein Abouzeid', 'PO_EMAI': 'aabouzei@nsf.gov', 'PO_PHON': '7032920000'}

Unmanned aerial vehicle (UAV)-enabled integrated sensing and communication (ISAC) have emerged as a promising technology for 6G wireless networks, aiming to improve user experience and enhance people’s lives. By leveraging millimeter wave (mmWave) communications, UAV-enabled ISAC systems are expected to deliver high-throughput, ultra-reliable, and low-latency wireless communications, along with highly accurate wireless sensing and localization within 6G networks. Simultaneously, artificial intelligence (AI) and machine learning (ML) are anticipated to transform platform-based ecosystems, business models, and services in future 6G networks. The key challenge is integrating UAV localization, mmWave communications, wireless sensing, and security with AI/ML for future 6G systems. A multidisciplinary team of six investigators from Auburn University (AU), Florida International University (FIU), the Indian Institute of Technology Kanpur (IIT Kharagpur), and the International Institute of Information Technology, Naya Raipur (IIIT, Naya Raipur) collaborate closely on a project focused on learning-assisted integrated sensing, communication, and security for 6G UAV networks. The educational plan of this project includes developing joint course materials on AI/ML for UAV networks and IoT, enhancing undergraduate and graduate-level courses at the participating institutions. Simulation tools and testbeds developed through this project offer students hands-on experience with cutting-edge technology. The project outcomes are disseminated via technical publications, conference keynotes/tutorials, IEEE distinguished lectures and seminars, a project website, and open-source repositories. The investigators are committed to encouraging participation from underrepresented groups through outreach programs at their institutions and the NSFBPC/REU/RET programs throughout the project.<br/><br/>The project aims to develop deep learning (DL)-based localization and sensing in UAV mmWave<br/>networks, location-aided UAV mmWave communications, and joint UAV mmWave communication and radar co-design to improve mmWave spectrum utilization, wireless sensing performance, and UAV device security. The research agenda consists of five well integrated thrusts: (i) Learning-based mmWave UAV localization and wireless sensing; (ii) Joint design of location-aided UAV mmWave communications and sensing; (iii) Multiple UAV communications and sensing co-design; (iv) Learning-based RF fingerprinting for UAV security; and (v) Integration and assessment: the proposed techniques are implemented with both ray-tracing software tools (e.g., DeepMIMO), mmWave devices (e.g., TP-link Talon AD7200) and TI mmWave radars, Parrot AR Drone2.0 UAV, programmable (e.g. USRP) devices, and the NSF PAWR AERPAW testbed, and validated with extensive experiments in real, representative outdoor and indoor environments.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/26/2024

08/26/2024

None

Grant

47.070, 47.079

1

4900

4900

2415208

{'FirstName': 'Shiwen', 'LastName': 'Mao', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Shiwen Mao', 'EmailAddress': 'smao@auburn.edu', 'NSF_ID': '000148324', 'StartDate': '08/26/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Auburn University', 'CityName': 'AUBURN', 'ZipCode': '368490001', 'PhoneNumber': '3348444438', 'StreetAddress': '321-A INGRAM HALL', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Alabama', 'StateCode': 'AL', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_ORG': 'AL03', 'ORG_UEI_NUM': 'DMQNDJDHTDG4', 'ORG_LGL_BUS_NAME': 'AUBURN UNIVERSITY', 'ORG_PRNT_UEI_NUM': 'DMQNDJDHTDG4'}

{'Name': 'Auburn University', 'CityName': 'AUBURN', 'StateCode': 'AL', 'ZipCode': '368495201', 'StreetAddress': '200 Broun Hall', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Alabama', 'CountryFlag': '1', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_PERF': 'AL03'}

[{'Code': '054Y00', 'Text': 'GVF - Global Venture Fund'}, {'Code': '164000', 'Text': 'Information Technology Researc'}]

2024~300000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2415208.xml'}

Collaborative Research: NSF-MeitY: CNS Core: Small: Learning-Assisted Integrated Sensing, Communication and Security for 6G UAV Networks

NSF

10/01/2024

09/30/2027

{'Value': 'Standard Grant'}

{'Code': '05050000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CNS', 'LongName': 'Division Of Computer and Network Systems'}}

{'SignBlockName': 'Alhussein Abouzeid', 'PO_EMAI': 'aabouzei@nsf.gov', 'PO_PHON': '7032920000'}

Unmanned aerial vehicle (UAV)-enabled integrated sensing and communication (ISAC) have emerged as a promising technology for 6G wireless networks, aiming to improve user experience and enhance people’s lives. By leveraging millimeter wave (mmWave) communications, UAV-enabled ISAC systems are expected to deliver high-throughput, ultra-reliable, and low-latency wireless communications, along with highly accurate wireless sensing and localization within 6G networks. Simultaneously, artificial intelligence (AI) and machine learning (ML) are anticipated to transform platform-based ecosystems, business models, and services in future 6G networks. The key challenge is integrating UAV localization, mmWave communications, wireless sensing, and security with AI/ML for future 6G systems. A multidisciplinary team of six investigators from Auburn University (AU), Florida International University (FIU), the Indian Institute of Technology Kanpur (IIT Kharagpur), and the International Institute of Information Technology, Naya Raipur (IIIT, Naya Raipur) collaborate closely on a project focused on learning-assisted integrated sensing, communication, and security for 6G UAV networks. The educational plan of this project includes developing joint course materials on AI/ML for UAV networks and IoT, enhancing undergraduate and graduate-level courses at the participating institutions. Simulation tools and testbeds developed through this project offer students hands-on experience with cutting-edge technology. The project outcomes are disseminated via technical publications, conference keynotes/tutorials, IEEE distinguished lectures and seminars, a project website, and open-source repositories. The investigators are committed to encouraging participation from underrepresented groups through outreach programs at their institutions and the NSFBPC/REU/RET programs throughout the project.<br/><br/>The project aims to develop deep learning (DL)-based localization and sensing in UAV mmWave<br/>networks, location-aided UAV mmWave communications, and joint UAV mmWave communication and radar co-design to improve mmWave spectrum utilization, wireless sensing performance, and UAV device security. The research agenda consists of five well integrated thrusts: (i) Learning-based mmWave UAV localization and wireless sensing; (ii) Joint design of location-aided UAV mmWave communications and sensing; (iii) Multiple UAV communications and sensing co-design; (iv) Learning-based RF fingerprinting for UAV security; and (v) Integration and assessment: the proposed techniques are implemented with both ray-tracing software tools (e.g., DeepMIMO), mmWave devices (e.g., TP-link Talon AD7200) and TI mmWave radars, Parrot AR Drone2.0 UAV, programmable (e.g. USRP) devices, and the NSF PAWR AERPAW testbed, and validated with extensive experiments in real, representative outdoor and indoor environments.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/26/2024

08/26/2024

None

Grant

47.070

1

4900

4900

2415209

{'FirstName': 'Xuyu', 'LastName': 'Wang', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Xuyu Wang', 'EmailAddress': 'xuywang@fiu.edu', 'NSF_ID': '000790164', 'StartDate': '08/26/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Florida International University', 'CityName': 'MIAMI', 'ZipCode': '331992516', 'PhoneNumber': '3053482494', 'StreetAddress': '11200 SW 8TH ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Florida', 'StateCode': 'FL', 'CONGRESSDISTRICT': '26', 'CONGRESS_DISTRICT_ORG': 'FL26', 'ORG_UEI_NUM': 'Q3KCVK5S9CP1', 'ORG_LGL_BUS_NAME': 'FLORIDA INTERNATIONAL UNIVERSITY', 'ORG_PRNT_UEI_NUM': 'Q3KCVK5S9CP1'}

{'Name': 'Florida International University', 'CityName': 'MIAMI', 'StateCode': 'FL', 'ZipCode': '331992516', 'StreetAddress': '11200 SW 8TH ST', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Florida', 'CountryFlag': '1', 'CONGRESSDISTRICT': '26', 'CONGRESS_DISTRICT_PERF': 'FL26'}

{'Code': '736300', 'Text': 'Networking Technology and Syst'}

2024~300000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2415209.xml'}

NSF-MeitY: NeTS: Small: Towards Learning Enabled Sustainable Service Handling in 6G

NSF

10/01/2024

09/30/2027

{'Value': 'Standard Grant'}

{'Code': '05050000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CNS', 'LongName': 'Division Of Computer and Network Systems'}}

{'SignBlockName': 'Alhussein Abouzeid', 'PO_EMAI': 'aabouzei@nsf.gov', 'PO_PHON': '7032920000'}

This is a collaborative project between universities in the United States and India to enable sustainable next generation cellular wireless (6G) services. Traditional approaches to resource allocation in wireless communications networks are based on mathematical models with known parameters. However, such models, along with the complete knowledge of the parameters, are unlikely to be available in 6G systems. An online learning paradigm capable of adapting to evolving and uncertain situations will prove invaluable in this scenario. The project develops learning-based control strategies for sustainable network operations with enhanced energy efficiency and improved resource usage in future mobile networks. The project also includes an innovative education plan contributing to workforce development from K-12 students to STEM and an innovative workforce development and training plan through short-term training programs for students and industry/working professionals. <br/><br/>The proposed research comprises three comprehensive thrusts and an evaluation plan. Thrust 1 focuses on creating a learning-based framework for resource allocation in the core network. Thrust 2 focuses on developing real-time resource allocation strategies for improving energy efficiency and sustainability in Radio Access Networks (RAN), with support for massive connectivity. Thrust 3 includes the development of an adaptive security mechanism for the 6G network. The algorithms developed in the project are implemented and evaluated on ns3-ai software integrated with learning capabilities, and a simulator and a testbed available at IIT Bombay.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/26/2024

08/26/2024

None

Grant

47.070, 47.079

1

4900

4900

2415213

{'FirstName': 'Shana', 'LastName': 'Moothedath', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Shana Moothedath', 'EmailAddress': 'mshana@iastate.edu', 'NSF_ID': '000869867', 'StartDate': '08/26/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Iowa State University', 'CityName': 'AMES', 'ZipCode': '500112103', 'PhoneNumber': '5152945225', 'StreetAddress': '1350 BEARDSHEAR HALL', 'StreetAddress2': '515 MORRILL ROAD', 'CountryName': 'United States', 'StateName': 'Iowa', 'StateCode': 'IA', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_ORG': 'IA04', 'ORG_UEI_NUM': 'DQDBM7FGJPC5', 'ORG_LGL_BUS_NAME': 'IOWA STATE UNIVERSITY OF SCIENCE AND TECHNOLOGY', 'ORG_PRNT_UEI_NUM': 'DQDBM7FGJPC5'}

{'Name': 'Iowa State University', 'CityName': 'AMES', 'StateCode': 'IA', 'ZipCode': '500112103', 'StreetAddress': '1350 BEARDSHEAR HALL', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Iowa', 'CountryFlag': '1', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_PERF': 'IA04'}

[{'Code': '054Y00', 'Text': 'GVF - Global Venture Fund'}, {'Code': '164000', 'Text': 'Information Technology Researc'}]

2024~372447

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2415213.xml'}

CNS Core: Small: NSF-MeitY: A Unified Framework for Video Analytics Optimization and Adaptation

NSF

09/01/2024

08/31/2027

{'Value': 'Standard Grant'}

{'Code': '05050000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CNS', 'LongName': 'Division Of Computer and Network Systems'}}

{'SignBlockName': 'Jason Hallstrom', 'PO_EMAI': 'jhallstr@nsf.gov', 'PO_PHON': '7032920000'}

Edge-cloud video analytics systems, also known as video analytics pipelines (VAPs), are being deployed in major cities around the world to support diverse applications, spanning public safety, transportation, healthcare, retail, and more. Unfortunately, the status quo of developing and deploying a VAP for a new application is largely manual and labor-intensive. (1) A VAP developer must implement end-to-end pipelines on heterogeneous hardware by writing low-level software for each component. (2) The developer must pick and choose the right set of machine learning models and their placements pre-deployment to minimize the cloud computing bill while providing acceptable latency and accuracy. (3) The developer must adapt the pipeline post-deployment in response to changes in the environment (e.g., network bandwidth, light conditions, traffic density). Each step is challenging to perform, presenting significant hurdles to the development and deployment of new VAP applications. This project aims to develop a unified framework to simplify and automate video analytics pipeline development, optimization, and adaptation by streamlining all three steps in developing and deploying a new VAP application. Under such a framework, application domain experts specify high-level analytics tasks (logical operators) to be performed on the camera frames and all candidate physical implementations for each logical operator (physical operators). Pipeline authors describe the pipelines via graphs, and the framework will automatically generate an optimal physical implementation for initial deployment and deploy an adaptation engine that monitors changes in environmental conditions and automates adaptation to new physical plans that satisfy application latency and accuracy constraints. <br/><br/>The project will have direct, practical implications to the video analytics industry and is poised for substantial societal impacts. (1) Impact on industry: The proposed VAP framework will advance the state-of-the-art by providing a much-needed solution that significantly eases the development effort of VAP vendors and shortens the time-to-deployment of new and increasingly diverse VAP applications. (2) Impact on society: The technologies developed for enabling the framework will foster wide adoption of important societal VAP applications, spanning transportation, healthcare, retail, public safety, and more. (3) Impact on other research fields: The work will have far-reaching impacts outside the area of video analytics systems by developing general query optimization techniques, which will also be applicable to traditional database management. The technologies developed in the project will be disseminated and transferred to the broader research community and the IT industry.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

07/10/2024

07/10/2024

None

Grant

47.070

1

4900

4900

2415216

{'FirstName': 'Charlie', 'LastName': 'Hu', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Charlie Hu', 'EmailAddress': 'ychu@purdue.edu', 'NSF_ID': '000118830', 'StartDate': '07/10/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Purdue University', 'CityName': 'WEST LAFAYETTE', 'ZipCode': '479061332', 'PhoneNumber': '7654941055', 'StreetAddress': '2550 NORTHWESTERN AVE # 1100', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Indiana', 'StateCode': 'IN', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_ORG': 'IN04', 'ORG_UEI_NUM': 'YRXVL4JYCEF5', 'ORG_LGL_BUS_NAME': 'PURDUE UNIVERSITY', 'ORG_PRNT_UEI_NUM': 'YRXVL4JYCEF5'}

{'Name': 'Purdue University', 'CityName': 'WEST LAFAYETTE', 'StateCode': 'IN', 'ZipCode': '479061332', 'StreetAddress': '2550 NORTHWESTERN AVE STE 1900', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Indiana', 'CountryFlag': '1', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_PERF': 'IN04'}

{'Code': '735400', 'Text': 'CSR-Computer Systems Research'}

2024~496895

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2415216.xml'}

Collaborative Research: Graph Learning, Generation, and Optimization with Highly Expressive Graph Neural Network Models

NSF

09/01/2024

08/31/2027

{'Value': 'Continuing Grant'}

{'Code': '03040000', 'Directorate': {'Abbreviation': 'MPS', 'LongName': 'Direct For Mathematical & Physical Scien'}, 'Division': {'Abbreviation': 'DMS', 'LongName': 'Division Of Mathematical Sciences'}}

{'SignBlockName': 'Tapabrata Maiti', 'PO_EMAI': 'tmaiti@nsf.gov', 'PO_PHON': '7032925307'}

In today's data-driven world, many complex systems can be represented as interconnected networks or graphs. This project aims to develop new methods for analyzing, generating, and optimizing these graph structures, with potential applications in areas such as social network analysis and molecular design. By improving the ability to learn from and work with graph-structured data, the project is expected to provide new tools for researchers across various scientific fields. The proposed research contributes to advancements in areas such as drug discovery, network analysis, and modeling of physical systems, offering new ways to approach complex problems in these domains. This project also offers research training opportunities for undergraduate and graduate students.<br/><br/>The project focuses on four main research areas: (1) developing more expressive and efficient graph neural networks, (2) creating improved generative models for graphs, (3) applying graph learning techniques to optimization problems, and (4) exploring the use of graph neural networks for discovering physical relations. The interconnected research thrusts aim to improve the capabilities of machine learning models based on graphs, laying the groundwork for solving complex graph-related challenges. The project will produce new mathematical and statistical tools, theoretical frameworks, and assessment methods for learning from graphs. The work is expected to advance graph learning techniques and their applications in scientific fields, providing researchers with new ways to handle data structured as graphs.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/20/2024

08/20/2024

None

Grant

47.070

1

4900

4900

2415226

{'FirstName': 'Yingnian', 'LastName': 'Wu', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Yingnian Wu', 'EmailAddress': 'ywu@stat.ucla.edu', 'NSF_ID': '000097763', 'StartDate': '08/20/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'University of California-Los Angeles', 'CityName': 'LOS ANGELES', 'ZipCode': '900244200', 'PhoneNumber': '3107940102', 'StreetAddress': '10889 WILSHIRE BLVD STE 700', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'California', 'StateCode': 'CA', 'CONGRESSDISTRICT': '36', 'CONGRESS_DISTRICT_ORG': 'CA36', 'ORG_UEI_NUM': 'RN64EPNH8JC6', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF CALIFORNIA, LOS ANGELES', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'University of California-Los Angeles', 'CityName': 'LOS ANGELES', 'StateCode': 'CA', 'ZipCode': '900951554', 'StreetAddress': '8971 Mathematical Sciences Building', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'California', 'CountryFlag': '1', 'CONGRESSDISTRICT': '36', 'CONGRESS_DISTRICT_PERF': 'CA36'}

{'Code': '808400', 'Text': 'CDS&E'}

2024~150000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2415226.xml'}

Collaborative Research: Graph Learning, Generation, and Optimization with Highly Expressive Graph Neural Network Models

NSF

09/01/2024

08/31/2027

{'Value': 'Continuing Grant'}

{'Code': '03040000', 'Directorate': {'Abbreviation': 'MPS', 'LongName': 'Direct For Mathematical & Physical Scien'}, 'Division': {'Abbreviation': 'DMS', 'LongName': 'Division Of Mathematical Sciences'}}

{'SignBlockName': 'Tapabrata Maiti', 'PO_EMAI': 'tmaiti@nsf.gov', 'PO_PHON': '7032925307'}

In today's data-driven world, many complex systems can be represented as interconnected networks or graphs. This project aims to develop new methods for analyzing, generating, and optimizing these graph structures, with potential applications in areas such as social network analysis and molecular design. By improving the ability to learn from and work with graph-structured data, the project is expected to provide new tools for researchers across various scientific fields. The proposed research contributes to advancements in areas such as drug discovery, network analysis, and modeling of physical systems, offering new ways to approach complex problems in these domains. This project also offers research training opportunities for undergraduate and graduate students.<br/><br/>The project focuses on four main research areas: (1) developing more expressive and efficient graph neural networks, (2) creating improved generative models for graphs, (3) applying graph learning techniques to optimization problems, and (4) exploring the use of graph neural networks for discovering physical relations. The interconnected research thrusts aim to improve the capabilities of machine learning models based on graphs, laying the groundwork for solving complex graph-related challenges. The project will produce new mathematical and statistical tools, theoretical frameworks, and assessment methods for learning from graphs. The work is expected to advance graph learning techniques and their applications in scientific fields, providing researchers with new ways to handle data structured as graphs.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/20/2024

08/20/2024

None

Grant

47.070

1

4900

4900

2415227

{'FirstName': 'Maggie', 'LastName': 'Cheng', 'PI_MID_INIT': 'X', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Maggie X Cheng', 'EmailAddress': 'maggie.cheng@iit.edu', 'NSF_ID': '000381985', 'StartDate': '08/20/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Illinois Institute of Technology', 'CityName': 'CHICAGO', 'ZipCode': '606163717', 'PhoneNumber': '3125673035', 'StreetAddress': '10 W 35TH ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Illinois', 'StateCode': 'IL', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_ORG': 'IL01', 'ORG_UEI_NUM': 'E2NDENMDUEG8', 'ORG_LGL_BUS_NAME': 'ILLINOIS INSTITUTE OF TECHNOLOGY', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Illinois Institute of Technology', 'CityName': 'CHICAGO', 'StateCode': 'IL', 'ZipCode': '606163717', 'StreetAddress': '10 W 35TH ST', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Illinois', 'CountryFlag': '1', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_PERF': 'IL01'}

{'Code': '808400', 'Text': 'CDS&E'}

2024~160338

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2415227.xml'}

NSF-BSF: Precision Engineering of Functional Polymers for High Performance Silica Scale Inhibitors in Reverse Osmosis Desalination

NSF

08/01/2024

07/31/2027

{'Value': 'Standard Grant'}

{'Code': '07020000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'CBET', 'LongName': 'Div Of Chem, Bioeng, Env, & Transp Sys'}}

{'SignBlockName': 'Karl Rockne', 'PO_EMAI': 'krockne@nsf.gov', 'PO_PHON': '7032927293'}

Reverse osmosis (RO) is recognized as the most energy-efficient seawater desalination technology. To address increasing societal demands for water, RO is being used more broadly for water recovery from unconventional sources such as brackish groundwater and industrial wastewater. Despite RO’s advantages, mineral scale formation on RO membranes remains a critical challenge as it adversely affects membrane performance and lifespan. Scale formation is even more problematic for unconventional RO applications. This is due to the increased prevalence of silica-based scales in unconventional water that are resistant to commonly used scale inhibitor chemicals. The goal of this project is to address this problem by developing effective inhibitors for silica scales through an international collaboration with researchers at Ben Gurion University (Israel). The project aims to develop molecular design principles for high-performing polymeric inhibitors. The work is guided by the principle that reactive silica acid-containing molecules polymerize to form clusters (i.e., “scale”) that cover the RO membrane. This scale can thus be controlled by polymeric inhibitors that stabilize silicic acids, thus limiting the rate of silica scale formation. The key to winning the chemical “battle” between silica scale deposition and polymer inhibition is to better understand the molecular-level interactions between the antiscaling polymers and the soluble silica species at the membrane interface. To that end, the project will investigate a host of polymer chemical and physical design properties, followed by synthesis and evaluation of attractive candidates. Successful completion of this project will benefit society by improving RO separation technology for increased water supply, as well as the promotion of clean energy technologies to address critical environmental challenges. Additional benefits to society result from teaching, mentoring, and outreach activities that will create educational opportunities for a diverse group of students to improve the Nation’s STEM workforce.<br/><br/>The development of precisely engineered polymers capable of inhibiting silica scale holds the potential to significantly improve the efficiency and extend the lifespan of RO membranes. The goal of this project is to elucidate the essential design principles for effective silica scale inhibitors under operational RO membrane conditions. The study will investigate the individual impact of polymer chain length, composition, and conformation on inhibition efficiency, as well as their detailed mechanistic role in stabilizing soluble silica species. Researchers will investigate scale formation utilizing a state-of-the-art quartz crystal microbalance in conjunction with localized surface plasmon resonance to elucidate mechanistic differences between homogeneous and membrane-based heterogeneous scaling processes. The research project encompasses functional polymer design and synthesis, antiscaling performance analysis in both homogeneous solutions and RO membranes, kinetic and computational studies on scaling and inhibition mechanisms, and the evaluation of RO desalination performance. The combined outcomes of this research will contribute to establishing a scalable and precise synthesis methodology for obtaining high-performance polymeric inhibitors for silica scaling.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/06/2024

08/06/2024

None

Grant

47.041

1

4900

4900

2415240

[{'FirstName': 'Menachem', 'LastName': 'Elimelech', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Menachem Elimelech', 'EmailAddress': 'menachem.elimelech@yale.edu', 'NSF_ID': '000207760', 'StartDate': '08/06/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Mingjiang', 'LastName': 'Zhong', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Mingjiang Zhong', 'EmailAddress': 'mingjiang.zhong@yale.edu', 'NSF_ID': '000749800', 'StartDate': '08/06/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}]

{'Name': 'Yale University', 'CityName': 'NEW HAVEN', 'ZipCode': '065113572', 'PhoneNumber': '2037854689', 'StreetAddress': '150 MUNSON ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Connecticut', 'StateCode': 'CT', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_ORG': 'CT03', 'ORG_UEI_NUM': 'FL6GV84CKN57', 'ORG_LGL_BUS_NAME': 'YALE UNIV', 'ORG_PRNT_UEI_NUM': 'FL6GV84CKN57'}

{'Name': 'Yale University', 'CityName': 'NEW HAVEN', 'StateCode': 'CT', 'ZipCode': '065118917', 'StreetAddress': '105 WALL ST', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Connecticut', 'CountryFlag': '1', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_PERF': 'CT03'}

{'Code': '144000', 'Text': 'EnvE-Environmental Engineering'}

2024~420000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2415240.xml'}

CPS: SMALL: NSF-MeitY: 5G Enabled Real-Time Digital Twins of Dynamic Construction Sites

NSF

09/01/2024

08/31/2027

{'Value': 'Standard Grant'}

{'Code': '07030000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'CMMI', 'LongName': 'Div Of Civil, Mechanical, & Manufact Inn'}}

{'SignBlockName': 'Siqian Shen', 'PO_EMAI': 'siqshen@nsf.gov', 'PO_PHON': '7032927048'}

This Cyber-Physical Systems (CPS) grant, a collaboration between the US National Science Foundation and the Ministry of Electronics and Information Technology of the Government of India (NSF-MeitY), supports research to develop a digital twin of dynamic environments such as construction sites using multiple unmanned aerial and ground robots equipped with cameras and 5G radios. This research can (a) enhance worker safety by identifying potential hazards and (b) improve construction efficiency by monitoring and optimizing resources devoted to different tasks. Technology emerging from this project can bring increased productivity in the construction industry, which has lagged behind other sectors such as manufacturing or agriculture. It can lead to affordable and green housing without compromising labor safety. To achieve these goals, the researchers will collaborate closely with multiple industry partners, and ensure public sharing of robotic data. This project will also work with the Philadelphia School District, which serves a primarily low-income and underrepresented minority population, to develop school curricula involving robotics and computer vision.<br/><br/>This project will build photometric, geometric, semantic, and radiometric representations of dynamic scenes using techniques from neural radiance fields and multi-modal visual-language features. Information-theoretic formulations of active perception and path planning will be used for monitoring construction progress and safety of human workers, using multi-robot teams. These algorithms will be run on aerial and ground robots along with edge servers that communicate periodically with these size, weight and power (SWaP)-constrained platforms using the latest standards in 5G. Using these algorithms, human workers carrying 5G radios can be localized using their radiometric signatures. Effectively, this project envisions a real-time perception and control stack executed on a heterogeneous multi-robot team. This research will be demonstrated using real-world experiments in Philadelphia and Bangalore (India).<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/09/2024

08/09/2024

None

Grant

47.041

1

4900

4900

2415249

[{'FirstName': 'R. Vijay', 'LastName': 'Kumar', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'R. Vijay Kumar', 'EmailAddress': 'Kumar@seas.upenn.edu', 'NSF_ID': '000280506', 'StartDate': '08/09/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Pratik', 'LastName': 'Chaudhari', 'PI_MID_INIT': 'A', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Pratik A Chaudhari', 'EmailAddress': 'pratikac@seas.upenn.edu', 'NSF_ID': '000806952', 'StartDate': '08/09/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Saurav', 'LastName': 'Agarwal', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Saurav Agarwal', 'EmailAddress': 'sauravag@seas.upenn.edu', 'NSF_ID': '000992260', 'StartDate': '08/09/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]

{'Name': 'University of Pennsylvania', 'CityName': 'PHILADELPHIA', 'ZipCode': '191046205', 'PhoneNumber': '2158987293', 'StreetAddress': '3451 WALNUT ST STE 440A', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Pennsylvania', 'StateCode': 'PA', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_ORG': 'PA03', 'ORG_UEI_NUM': 'GM1XX56LEP58', 'ORG_LGL_BUS_NAME': 'TRUSTEES OF THE UNIVERSITY OF PENNSYLVANIA, THE', 'ORG_PRNT_UEI_NUM': 'GM1XX56LEP58'}

{'Name': 'University of Pennsylvania', 'CityName': 'PHILADELPHIA', 'StateCode': 'PA', 'ZipCode': '191043409', 'StreetAddress': '3330 Walnut Street', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Pennsylvania', 'CountryFlag': '1', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_PERF': 'PA03'}

{'Code': '791800', 'Text': 'CPS-Cyber-Physical Systems'}

2024~499889

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2415249.xml'}

Conference: FASEB 2024 Conference on Genetic Recombination and Genome Rearrangements

NSF

07/01/2024

06/30/2025

{'Value': 'Standard Grant'}

{'Code': '08070000', 'Directorate': {'Abbreviation': 'BIO', 'LongName': 'Direct For Biological Sciences'}, 'Division': {'Abbreviation': 'MCB', 'LongName': 'Div Of Molecular and Cellular Bioscience'}}

{'SignBlockName': 'Clifford Weil', 'PO_EMAI': 'cweil@nsf.gov', 'PO_PHON': '7032924668'}

This award is for support of the conference Genetic Recombination and Genome Rearrangements, to be held July 14-19 2024 in Tucson, Arizona. This is a well-established conference that has occurred biennially since 1985. The meeting will include 8 plenary sessions, each of which will have 5 to 8 20 minute presentations. Approximately two-thirds of the speakers are by invitation, and the remainder will be selected from contributed abstracts, with an emphasis on early career scientists. In addition, approximately 70 junior participants giving posters will also be giving short Poster Primer talks, introducing themselves and their poster topics. This meeting will have over 200 participants representing all career stages, from trainees to established PI’s. The organizing committee will make a special effort to provide plenary speaking opportunities to diverse junior scientists as well. Notably, all NSF funds will be used to support participation by trainees and young investigators, with an emphasis on those from historically underrepresented groups as well as those with financial need.&lt;br/&gt;&lt;br/&gt;The conference will focus on the topic of recombination and its implications for genome rearrangement, mutation, DNA repair and chromosome function. These topics will be explored from multiple, mechanistic perspectives, including structural and biophysical analyses of the proteins involved in recombination, and genomic analyses of the consequences of recombination for genome structure. The meeting will emphasize breakthroughs spurred by cutting-edge approaches using molecular genetics, biochemistry and structural biology, as applied to DNA damage responses, chromatin remodeling, and the general processes of replication, transcription and recombination.&lt;br/&gt;&lt;br/&gt;This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

01/12/2024

01/12/2024

None

Grant

47.074

1

4900

4900

2415260

{'FirstName': 'Anna', 'LastName': 'Malkova', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Anna Malkova', 'EmailAddress': 'anna-malkova@uiowa.edu', 'NSF_ID': '000913281', 'StartDate': '01/12/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Federation of Amer Societies For Exper Biology', 'CityName': 'ROCKVILLE', 'ZipCode': '208529839', 'PhoneNumber': '3016347013', 'StreetAddress': '6120 EXECUTIVE BLVD STE 575', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Maryland', 'StateCode': 'MD', 'CONGRESSDISTRICT': '08', 'CONGRESS_DISTRICT_ORG': 'MD08', 'ORG_UEI_NUM': 'CLHCSTHHSX25', 'ORG_LGL_BUS_NAME': 'FEDERATION OF AMERICAN SOCIETIES FOR EXPERIMENTAL BIOLOGY', 'ORG_PRNT_UEI_NUM': 'PTK7AJZVT7C1'}

{'Name': 'Federation of Amer Societies For Exper Biology', 'CityName': 'ROCKVILLE', 'StateCode': 'MD', 'ZipCode': '208524905', 'StreetAddress': '6120 EXECUTIVE BLVD', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Maryland', 'CountryFlag': '1', 'CONGRESSDISTRICT': '08', 'CONGRESS_DISTRICT_PERF': 'MD08'}

{'Code': '1112', 'Text': 'Genetic Mechanisms'}

2024~16000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2415260.xml'}

Collaborative Research: NSF-MeitY: NeuroFlex: RRAM-Enhanced Neural Interfaces for Reconfigurable Implantable Machine Intelligence

NSF

08/01/2024

07/31/2027

{'Value': 'Standard Grant'}

{'Code': '07010000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'ECCS', 'LongName': 'Div Of Electrical, Commun & Cyber Sys'}}

{'SignBlockName': 'Ale Lukaszew', 'PO_EMAI': 'rlukasze@nsf.gov', 'PO_PHON': '7032928103'}

Understanding the brain is one of the greatest challenges in science and engineering. Current brain-machine interfaces, however, are severely limited by power consumption, data acquisition capabilities, and real-time processing constraints. These limitations in turn limit our ability to study brain function and develop treatments for neurological disorders. The NeuroFlex project aims to address these challenges by creating a powerful yet energy-efficient neural interface platform. By combining innovative memory devices optimized for efficient data storage, programmable circuits for high-density neural signal acquisition, and specialized processors for low-power computation, this research could revolutionize our understanding of the brain. The insights gained from this advanced neural interface technology have the potential to unlock new therapies for conditions like epilepsy, Parkinson's disease, and other neurological disorders that affect millions worldwide. Furthermore, the interdisciplinary nature of this project, spanning device engineering, circuit design, and tensor accelerators, will advance these fields and inspire new avenues of research. The project will also develop new tools and educational initiatives. The researchers will organize a workshop on computing with emerging technologies, develop curriculum modules on system-on-chip design, and engage K-12 students through outreach activities aimed at encouraging participation in STEM fields, with a focus on underrepresented groups.<br/><br/>The NeuroFlex project will develop an implantable neural interface platform that integrates three key innovations: 1) optimized resistive RAM memory for efficient data storage, 2) programmable analog front-end circuits for high-density neural signal acquisition, and 3) specialized processors for energy-efficient computation of both dense and sparse neural network operations. Intelligent control algorithms and software will orchestrate the flow of data through these components to maximize efficiency within the strict power and size constraints of an implantable device. The research plan encompasses device fabrication and characterization, mixed-signal circuit design, digital accelerator development, and the mapping of machine learning algorithms onto the novel hardware architecture. We will validate our approach through testing of two prototype chips, including one with novel integrated devices. By bringing together experts in devices, circuits, architectures, and algorithms, the NeuroFlex project aims to bridge the gap between neuroengineering and microelectronics to enable a new generation of brain-machine interface technologies.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

06/25/2024

06/25/2024

None

Grant

47.041

1

4900

4900

2415261

{'FirstName': 'Siddharth', 'LastName': 'Joshi', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Siddharth Joshi', 'EmailAddress': 'sjoshi2@nd.edu', 'NSF_ID': '000788786', 'StartDate': '06/25/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'University of Notre Dame', 'CityName': 'NOTRE DAME', 'ZipCode': '465565708', 'PhoneNumber': '5746317432', 'StreetAddress': '940 GRACE HALL', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Indiana', 'StateCode': 'IN', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_ORG': 'IN02', 'ORG_UEI_NUM': 'FPU6XGFXMBE9', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF NOTRE DAME DU LAC', 'ORG_PRNT_UEI_NUM': 'FPU6XGFXMBE9'}

{'Name': 'University of Notre Dame', 'CityName': 'NOTRE DAME', 'StateCode': 'IN', 'ZipCode': '465565708', 'StreetAddress': '940 Grace Hall', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Indiana', 'CountryFlag': '1', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_PERF': 'IN02'}

{'Code': '756400', 'Text': 'CCSS-Comms Circuits & Sens Sys'}

2024~319999

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2415261.xml'}

Collaborative Research: NSF-MeitY: NeuroFlex: RRAM-Enhanced Neural Interfaces for Reconfigurable Implantable Machine Intelligence

NSF

08/01/2024

07/31/2027

{'Value': 'Standard Grant'}

{'Code': '07010000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'ECCS', 'LongName': 'Div Of Electrical, Commun & Cyber Sys'}}

{'SignBlockName': 'Ale Lukaszew', 'PO_EMAI': 'rlukasze@nsf.gov', 'PO_PHON': '7032928103'}

Understanding the brain is one of the greatest challenges in science and engineering. Current brain-machine interfaces, however, are severely limited by power consumption, data acquisition capabilities, and real-time processing constraints. These limitations in turn limit our ability to study brain function and develop treatments for neurological disorders. The NeuroFlex project aims to address these challenges by creating a powerful yet energy-efficient neural interface platform. By combining innovative memory devices optimized for efficient data storage, programmable circuits for high-density neural signal acquisition, and specialized processors for low-power computation, this research could revolutionize our understanding of the brain. The insights gained from this advanced neural interface technology have the potential to unlock new therapies for conditions like epilepsy, Parkinson's disease, and other neurological disorders that affect millions worldwide. Furthermore, the interdisciplinary nature of this project, spanning device engineering, circuit design, and tensor accelerators, will advance these fields and inspire new avenues of research. The project will also develop new tools and educational initiatives. The researchers will organize a workshop on computing with emerging technologies, develop curriculum modules on system-on-chip design, and engage K-12 students through outreach activities aimed at encouraging participation in STEM fields, with a focus on underrepresented groups.<br/><br/>The NeuroFlex project will develop an implantable neural interface platform that integrates three key innovations: 1) optimized resistive RAM memory for efficient data storage, 2) programmable analog front-end circuits for high-density neural signal acquisition, and 3) specialized processors for energy-efficient computation of both dense and sparse neural network operations. Intelligent control algorithms and software will orchestrate the flow of data through these components to maximize efficiency within the strict power and size constraints of an implantable device. The research plan encompasses device fabrication and characterization, mixed-signal circuit design, digital accelerator development, and the mapping of machine learning algorithms onto the novel hardware architecture. We will validate our approach through testing of two prototype chips, including one with novel integrated devices. By bringing together experts in devices, circuits, architectures, and algorithms, the NeuroFlex project aims to bridge the gap between neuroengineering and microelectronics to enable a new generation of brain-machine interface technologies.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

06/25/2024

06/25/2024

None

Grant

47.041

1

4900

4900

2415262

{'FirstName': 'Rajit', 'LastName': 'Manohar', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Rajit Manohar', 'EmailAddress': 'rajit.manohar@yale.edu', 'NSF_ID': '000487009', 'StartDate': '06/25/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Yale University', 'CityName': 'NEW HAVEN', 'ZipCode': '065113572', 'PhoneNumber': '2037854689', 'StreetAddress': '150 MUNSON ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Connecticut', 'StateCode': 'CT', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_ORG': 'CT03', 'ORG_UEI_NUM': 'FL6GV84CKN57', 'ORG_LGL_BUS_NAME': 'YALE UNIV', 'ORG_PRNT_UEI_NUM': 'FL6GV84CKN57'}

{'Name': 'Yale University', 'CityName': 'NEW HAVEN', 'StateCode': 'CT', 'ZipCode': '065116810', 'StreetAddress': '10 Hillhouse Avenue', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Connecticut', 'CountryFlag': '1', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_PERF': 'CT03'}

{'Code': '756400', 'Text': 'CCSS-Comms Circuits & Sens Sys'}

2024~330000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2415262.xml'}

Developing Customary Law in Systems of Legal Pluralism

NSF

08/01/2024

07/31/2027

{'Value': 'Standard Grant'}

{'Code': '04050000', 'Directorate': {'Abbreviation': 'SBE', 'LongName': 'Direct For Social, Behav & Economic Scie'}, 'Division': {'Abbreviation': 'SES', 'LongName': 'Divn Of Social and Economic Sciences'}}

{'SignBlockName': 'Susan F. Hirsch', 'PO_EMAI': 'shirsch@nsf.gov', 'PO_PHON': '7032922950'}

Legal pluralism, the coexistence of multiple legal systems within one society, is practiced in more than forty countries worldwide, often where customary law coexists with legal systems transplanted during colonization. Customary law courts generally address local issues such as marriage, land rights, inheritance, and inter-group conflicts. They tend to emphasize community participation and apply informal, dispute resolution processes that yield restorative decisions designed to support and heal individuals and communities. By contrast, formal courts (often based on Western legal traditions) employ official processes, focus on individuals, and emphasize retributive justice. These courts are intended to anchor a unified state legal system that serves governance, business development, and ties to the global community, If not well managed, the coexistence of multiple legal options can produce contradiction, uncertainty, and institutional weakness and can disadvantage the livelihoods of individuals and communities. The scientific study of legal pluralism, as exemplified in this project, identifies the advantages and limitations of legal pluralism by documenting and collaboratively developing customary law in relation to a state system. The case study model produced through this research illuminates how customary law’s guiding principles might underpin a legal system built on both longstanding customary practices and globally-recognized essential rights. The findings inform efforts to combine informal and formal legal options effectively in many contexts of legal pluralism, including the United States, where efforts to incorporate restorative justice options into the formal, retributive-based system are ongoing. <br/><br/>This project expands on an ethnographic study of customary courts initiated in 2008 in response to an official call for increased reliance on customary law. One intended aim was to address violence and lawlessness in a locally-relevant manner. The research team will observe and document court cases in multiple contexts, including a formal District Court, to establish a database recording the application and adaptation of customary law across one local area. The database will be used to develop and refine theories of legal pluralism, including the challenges of facilitating collaboration between different legal systems, when one employs restorative justice and the other retributive justice. The research team includes locally-based formal and customary law experts, and the research design includes participatory opportunities for local collaboration in data analysis, including by sitting magistrates. Finally, the efficacy of customary courts for establishing peace after communal warfare with contemporary weapons will be investigated by monitoring peace negotiations and their incorporation of customary principles. An important product of these efforts will be a guidebook to customary law to be used to train new customary court magistrates and provide a resource for formal court personnel, law enforcement personnel, public servants and students and a model for such guidebooks for other contexts. Results of the in-depth study of this initiative will be relevant to the challenges of developing effective systems of legal pluralism in other nations worldwide.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

07/19/2024

07/19/2024

None

Grant

47.075

1

4900

4900

2415284

{'FirstName': 'Pauline', 'LastName': 'Wiessner', 'PI_MID_INIT': 'W', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Pauline W Wiessner', 'EmailAddress': 'wiessner@soft-link.com', 'NSF_ID': '000791367', 'StartDate': '07/19/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'University of Utah', 'CityName': 'SALT LAKE CITY', 'ZipCode': '841129049', 'PhoneNumber': '8015816903', 'StreetAddress': '201 PRESIDENTS CIR', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Utah', 'StateCode': 'UT', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_ORG': 'UT01', 'ORG_UEI_NUM': 'LL8GLEVH6MG3', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF UTAH', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'University of Utah', 'CityName': 'SALT LAKE CITY', 'StateCode': 'UT', 'ZipCode': '841129049', 'StreetAddress': '201 PRESIDENTS CIR', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Utah', 'CountryFlag': '1', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_PERF': 'UT01'}

[{'Code': '128Y00', 'Text': 'Law & Science'}, {'Code': '139000', 'Text': 'Cultural Anthropology'}]

2024~206134

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2415284.xml'}

EAGER: IMPRESS-U: Exploratory Research in Robust Machine Learning for Object Detection and Classification

NSF

05/01/2024

04/30/2026

{'Value': 'Standard Grant'}

{'Code': '01090000', 'Directorate': {'Abbreviation': 'O/D', 'LongName': 'Office Of The Director'}, 'Division': {'Abbreviation': 'OISE', 'LongName': 'Office Of Internatl Science &Engineering'}}

{'SignBlockName': 'Maija Kukla', 'PO_EMAI': 'mkukla@nsf.gov', 'PO_PHON': '7032924940'}

This project is jointly supported by NSF, Estonian Research Council (ETAG), US National Academy of Sciences, and Office of Naval Research Global (DoD). <br/><br/>The multilateral partnership team (Rochester Institute of Technology, USA, the National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute", Ukraine, and Tallinn Technical University, Estonia) will advance scientific knowledge in machine learning and computer vision. It is expected that the obtained findings will contribute to foundations in analysis and design of modern engineered semi-autonomous and autonomous systems, as well as control and machine intelligence. This project targets a range of educational and learning activities, fostering: (1) Multidisciplinary faculty, researchers and students experience, scholarship and knowledge generation; (2) Competitiveness and national security by transformative research and global diverse education in critical areas of recognized needs, opportunities and urgency; (3) Knowledge and research findings implementation, disseminations and institutionalization; (4) Building a diverse research team, and advancing early-carrier faculty, including underrepresented groups; (5) State-of-the-art ecosystem by integrating research and education; (6) A modern globally-competitive research workforce in critical areas of national economy and security.<br/><br/>Multi-university research team will conduct exploratory transformative research, addressing open problems in adaptive machine learning, computer vision, object detection and classification. The researchers will investigate reduced-dimensionality convolutional neural networks to ensure high mean average precision, object detection probability, classification accuracy, robustness to nefarious data, and high speed. Adaptive machine learning will be empowered by applying singular value factorization analytics, supported by a calculus of compact multidimensional operator spaces. The proposed concept should guarantee content-aware information-dense data analytics, dimensionality and parameter reduction, robust image reconstruction, as well as information perception. Computationally efficient machine learning models will be trained on standard and custom datasets. Novel objective functions and algorithms will be investigated evaluating performance metrics and benchmarks.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

02/12/2024

02/12/2024

None

Grant

47.079

1

4900

4900

2415299

[{'FirstName': 'Leon', 'LastName': 'Reznik', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Leon Reznik', 'EmailAddress': 'lr@cs.rit.edu', 'NSF_ID': '000491457', 'StartDate': '02/12/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Sergey', 'LastName': 'Lyshevski', 'PI_MID_INIT': 'E', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Sergey E Lyshevski', 'EmailAddress': 'seleee@rit.edu', 'NSF_ID': '000292001', 'StartDate': '02/12/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}]

{'Name': 'Rochester Institute of Tech', 'CityName': 'ROCHESTER', 'ZipCode': '146235603', 'PhoneNumber': '5854757987', 'StreetAddress': '1 LOMB MEMORIAL DR', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'New York', 'StateCode': 'NY', 'CONGRESSDISTRICT': '25', 'CONGRESS_DISTRICT_ORG': 'NY25', 'ORG_UEI_NUM': 'J6TWTRKC1X14', 'ORG_LGL_BUS_NAME': 'ROCHESTER INSTITUTE OF TECHNOLOGY', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Rochester Institute of Tech', 'CityName': 'ROCHESTER', 'StateCode': 'NY', 'ZipCode': '146235603', 'StreetAddress': '1 LOMB MEMORIAL DR', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'New York', 'CountryFlag': '1', 'CONGRESSDISTRICT': '25', 'CONGRESS_DISTRICT_PERF': 'NY25'}

{'Code': '729800', 'Text': 'International Research Collab'}

2024~49997

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2415299.xml'}

SBIR Phase I: Variable Machines

NSF

08/15/2024

07/31/2025

{'Value': 'Standard Grant'}

{'Code': '15030000', 'Directorate': {'Abbreviation': 'TIP', 'LongName': 'Dir for Tech, Innovation, & Partnerships'}, 'Division': {'Abbreviation': 'TI', 'LongName': 'Translational Impacts'}}

{'SignBlockName': 'Vincent Lee', 'PO_EMAI': 'vinlee@nsf.gov', 'PO_PHON': '7032925041'}

The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase I project aims to drastically reduce the cost, lead time, and material waste associated with large format additive manufacturing. This is achieved through the development of a reconfigurable print bed composed of an array of linear actuators, which can be individually adjusted in height thereby eliminating the need for a printed support structure. Additive manufacturing plays a critical role in R&D, and small volume manufacturing across the aerospace, renewable energy, automotive, and maritime industries. This technology will be instrumental in stirring innovation across these industries by enabling faster, more efficient rapid prototyping, and unlocking additive manufacturing as a viable mass manufacturing process. This technology is estimated to save manufacturers on the order of $1.1M in material costs per year, while requiring only 30% of the capital expenditure of existing large format additive manufacturing technologies.<br/><br/>This Small Business Innovation Research (SBIR) Phase I project entails the design of a reconfigurable additive manufacturing print bed composed of an array of linear actuators, where each actuator is capable of sub 10 micron closed loop position feedback, and a pneumatic end effector capable of contact detection. A pair of these actuator arrays will be built, including the development of the embedded and front-end control software necessary to program them for a variety of tasks such as additive manufacturing and dynamic work holding. These actuator arrays will then be integrated with existing large format additive and subtractive manufacturing platforms, as well as an internally developed hybrid additive CNC tool. Particular research and development efforts will focus on early layer print process, where bridging between actuator end effectors will require non-planar slicing and control algorithms. Parts printed with this technology will be characterized to adjust process parameters and improve their final mechanical and thermal material properties.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/06/2024

08/06/2024

None

Grant

47.084

1

4900

4900

2415303

{'FirstName': 'David', 'LastName': 'Preiss', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'David Preiss', 'EmailAddress': 'davepreiss@gmail.com', 'NSF_ID': '000987575', 'StartDate': '08/06/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'VARIABLES MACHINES COMPANY', 'CityName': 'SOMERVILLE', 'ZipCode': '021431209', 'PhoneNumber': '2158509014', 'StreetAddress': '34 MADISON ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Massachusetts', 'StateCode': 'MA', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_ORG': 'MA07', 'ORG_UEI_NUM': 'TDJXE5LLS6K5', 'ORG_LGL_BUS_NAME': 'VARIABLES MACHINES COMPANY', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'VARIABLES MACHINES COMPANY', 'CityName': 'SOMERVILLE', 'StateCode': 'MA', 'ZipCode': '021431209', 'StreetAddress': '34 MADISON ST', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Massachusetts', 'CountryFlag': '1', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_PERF': 'MA07'}

{'Code': '537100', 'Text': 'SBIR Phase I'}

2024~274579

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2415303.xml'}

STTR Phase I: AAV QC using SANE Sensor

NSF

07/01/2024

06/30/2025

{'Value': 'Standard Grant'}

{'Code': '15030000', 'Directorate': {'Abbreviation': 'TIP', 'LongName': 'Dir for Tech, Innovation, & Partnerships'}, 'Division': {'Abbreviation': 'TI', 'LongName': 'Translational Impacts'}}

{'SignBlockName': 'Henry Ahn', 'PO_EMAI': 'hahn@nsf.gov', 'PO_PHON': '7032927069'}

The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase I project is it will demonstrate a plasmonic nanopore sensor device for all-in-one DNA loading characterization of adeno-associated viruses (AAVs) used for gene therapy. In the longer-term, the company anticipates that it will extend uses of this device to accurately test the drug or DNA/RNA loading consistency of soft nanoparticles such as exosomes, other viruses, and liposomes, to make this quality control (QC) technology applicable to all nanoparticles with biological applications and beyond. This project has inextricable interests in biochemistry, nanoengineering, photonics, and resistive pulse sensing which would be beneficial to encourage more students to pursue STEM degree through its outreach program. The PI will lead the company’s outreach in the Dallas County Community College District, whose mission is to build up the local workforce to today’s market needs, with nanosensor demonstrations and discussion of broad applications. The proposed technology also has the potential to drastically reduce the time and resource demands of AAV QC processes and increase success rates in early-phase gene therapy trials, accelerating FDA approvals for desperately needed treatments. <br/><br/>This Small Business Technology Transfer (STTR) Phase I project will demonstrate a plasmonic nanopore sensor device that will outperform existing analytical techniques by capturing multiple optical-electrical data types per AAV particle to enable, for the first time, unambiguous payload classification (single-stranded DNA versus double-stranded DNA, or empty) at low, pre-scale-up concentrations to optimize formulations in small batches, enabling significant savings in subsequent large-volume production. The proposed work will show feasibility of the proposed device to be nanofabricated in a scalable manner by electron beam lithography, namely optimize sensor nanofabrication protocol for accuracy and production reproducibility of the 3D plasmonic trap, and ensure accurate laser source alignment with bonded optics, and a photodetector collecting optical signals transmitted through the sensor. In addition, this work will optimize machine learning-based sensor discrimination between empty versus partly and fully loaded AAVs by optimizing the spectrum of AC pulse frequencies that scan each particle during trapping. Once successfully tested, the prototype’s nanofabrication and machine-learning workflows will be ready for further development into the company’s first commercial device after a subsequent Phase II.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

06/12/2024

06/12/2024

None

Grant

47.084

1

4900

4900

2415309

[{'FirstName': 'Scott', 'LastName': 'Renkes', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Scott Renkes', 'EmailAddress': 'renkessa@gmail.com', 'NSF_ID': '000980969', 'StartDate': '06/12/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Georgios', 'LastName': 'Alexandrakis', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Georgios Alexandrakis', 'EmailAddress': 'galex@uta.edu', 'NSF_ID': '000553083', 'StartDate': '06/12/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]

{'Name': 'ADAVANCE NANOLYTICS INC', 'CityName': 'DALLAS', 'ZipCode': '752482201', 'PhoneNumber': '7402726710', 'StreetAddress': '7223 ARBOR OAKS DR', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Texas', 'StateCode': 'TX', 'CONGRESSDISTRICT': '24', 'CONGRESS_DISTRICT_ORG': 'TX24', 'ORG_UEI_NUM': 'GVL5CSKS4EW5', 'ORG_LGL_BUS_NAME': 'ADAVANCE NANOLYTICS INC', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Adavance Nanolytics Inc', 'CityName': 'Arlington', 'StateCode': 'TX', 'ZipCode': '760101511', 'StreetAddress': '500 UTA Blvd, ERB 182A', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Texas', 'CountryFlag': '1', 'CONGRESSDISTRICT': '33', 'CONGRESS_DISTRICT_PERF': 'TX33'}

{'Code': '150500', 'Text': 'STTR Phase I'}

2024~275000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2415309.xml'}

Conference: 2024 NanoFlorida Conference: New Frontiers in Nanoscale interactions

NSF

04/01/2024

03/31/2025

{'Value': 'Standard Grant'}

{'Code': '07020000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'CBET', 'LongName': 'Div Of Chem, Bioeng, Env, & Transp Sys'}}

{'SignBlockName': 'Nora Savage', 'PO_EMAI': 'nosavage@nsf.gov', 'PO_PHON': '7032927949'}

Nanotechnology research and commercialized products are increasing their presence and being integrated into society and will likely remain at the forefront of scientific discoveries and applications for the next decade and beyond. Advancing nanoscience and disseminating the advances in the field remains a pivotal need. To this end, the Florida Association for Nanotechnology founded in 2019, creates a collaborative network of researchers, faculty, industry affiliates, and students in the diverse fields of nanoscience and nanotechnology. Herein proposes to conduct its annual NanoFlorida Conference to be held on April 20-21, 2024, in Tallahassee, Florida, hosted jointly by Florida State University and Florida Agricultural and Mechanical University. The conference aims are: i) to discuss advances in the understanding of nanoscale interaction, processing and awareness, and ii) provide a platform for scientific exchange with a focus on enhancing student and postdoc participation in the conference. Having extensive experience in organizing professional student conferences, the Principal Investigator will utilize post-conference surveys and publications of presenters’ research to measure the success of this year’s conference objectives. Conference will feature and promote collaborative and interdisciplinary research by hosting presentations by experts in the field, and providing new insights into nanoscale interactions for nanoscientists, clinicians, and engineers, and expanding multidisciplinary STEM education toward the next generation workforce. &lt;br/&gt;&lt;br/&gt;The annual NanoFlorida Conference, which aims to promote and increase awareness of nanotechnology applications and nanoscale interactions, will be held in Tallahassee, FL on April 20-21, 2024, hosted by Florida State University and Florida Agricultural and Mechanical University. This year’s conference will include symposia on advances in nanoscale interactions, artificial intelligence in nanotechnology, nanomaterials, and devices for biosensing, and their applications in energy, medicine, agriculture, and space sciences; and provide new opportunities for students to network with researchers from academic institutions and the broader nanotechnology industry. The Conference will use funds to support presenters ensuring diversity, inclusion, access, and equity in selecting these students, postdocs, and faculty participants and oral or poster presentations. Conference objectives encompass promoting collaborative and interdisciplinary research, expanding multidisciplinary education and research projects, hosting presentations by experts in the field, and providing new insights into nanoscale interactions for nanoscientists, clinicians, and engineers. Students will have the opportunity to meet researchers from other institutions and industry settings, forming professional relationships that provide long-term benefits to advance their STEM education and careers.&lt;br/&gt;&lt;br/&gt;This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

04/03/2024

04/03/2024

None

Grant

47.041

1

4900

4900

2415310

{'FirstName': 'Shyam', 'LastName': 'Mohapatra', 'PI_MID_INIT': 'S', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Shyam S Mohapatra', 'EmailAddress': 'Fan.network.info@gmail.com', 'NSF_ID': '000991426', 'StartDate': '04/03/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'FLORIDA ASSOCIATION FOR NANOBIOTECHNOLOGY, INC', 'CityName': 'LUTZ', 'ZipCode': '335584864', 'PhoneNumber': '8133124248', 'StreetAddress': '16704 TOBACCO RD', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Florida', 'StateCode': 'FL', 'CONGRESSDISTRICT': '14', 'CONGRESS_DISTRICT_ORG': 'FL14', 'ORG_UEI_NUM': 'WTCDCM9B8BP6', 'ORG_LGL_BUS_NAME': 'FLORIDA ASSOCIATION FOR NANOBIOTECHNOLOGY, INC', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'FLORIDA ASSOCIATION FOR NANOBIOTECHNOLOGY, INC', 'CityName': 'LUTZ', 'StateCode': 'FL', 'ZipCode': '335584864', 'StreetAddress': '16704 TOBACCO RD', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Florida', 'CountryFlag': '1', 'CONGRESSDISTRICT': '14', 'CONGRESS_DISTRICT_PERF': 'FL14'}

{'Code': '1179', 'Text': 'Nanoscale Interactions Program'}

2024~30000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2415310.xml'}

SBIR Phase I: Continuous Identity Verification via Wearable Neural Interfaces

NSF

09/01/2024

02/28/2025

{'Value': 'Standard Grant'}

{'Code': '15030000', 'Directorate': {'Abbreviation': 'TIP', 'LongName': 'Dir for Tech, Innovation, & Partnerships'}, 'Division': {'Abbreviation': 'TI', 'LongName': 'Translational Impacts'}}

{'SignBlockName': 'Peter Atherton', 'PO_EMAI': 'patherto@nsf.gov', 'PO_PHON': '7032928772'}

The broader impact of this Small Business Innovation Research (SBIR) Phase I project is to enhance digital security by integrating continuous biometric authentication into all human-computer interactions. The World Economic Forum cites widespread cyber-crime among the top 10 most severe global risks, with widespread impact on private industry, critical infrastructure, and cyber warfare. Recent developments in artificial intelligence compound these risks, with “deepfake” technology and Large Language models producing highly convincing fraudulent communications that easily bypass human scrutiny. This project develops and evaluates a new form of real-time authentication based on a novel biometric sensing approach that can secure every interaction an individual has with digital systems. At scale, the technology can mitigate cyber threats to secured systems by continuously certifying the authenticity of human-computer interactions.<br/><br/>This Small Business Innovation Research (SBIR) Phase I project will commercialize a fundamentally new biometric authentication approach for secure human-computer interaction. When interfacing with digital technology, there is no direct link between a user’s actions and their identity. Current approaches to solve this problem (e.g., usernames, passwords, biometrics) are imperfect, presenting a major weak point in digital security that is commonly exploited. As humans interact with technology, their hand movements and posture arise from unique neuromuscular activity patterns that could be used for real-time identity verification. This project develops sensing technology to capture these unique signals to create a new kind of continuous, biometric authentication. This approach essentially provides a user-specific “watermark” that the wearer’s actions (keystrokes, gestures, etc.) are authentic and authorized. Real-time user verification can streamline the authentication process and overcome core vulnerabilities in legacy approaches that make them susceptible to compromise, setting the stage for secure and intuitive human-machine interfacing.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/22/2024

08/22/2024

None

Grant

47.084

1

4900

4900

2415318

{'FirstName': 'William', 'LastName': 'Liberti', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'William Liberti', 'EmailAddress': 'will@mneuro.tech', 'NSF_ID': '000975114', 'StartDate': '08/22/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'MORPHOSIS INC', 'CityName': 'BERKELEY', 'ZipCode': '947081603', 'PhoneNumber': '6175290762', 'StreetAddress': '1152 EUCLID AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'California', 'StateCode': 'CA', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_ORG': 'CA12', 'ORG_UEI_NUM': 'GP1SFMCM9GF3', 'ORG_LGL_BUS_NAME': 'MORPHOSIS INC', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'MORPHOSIS INC', 'CityName': 'BERKELEY', 'StateCode': 'CA', 'ZipCode': '947081603', 'StreetAddress': '1152 EUCLID AVE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'California', 'CountryFlag': '1', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_PERF': 'CA12'}

{'Code': '537100', 'Text': 'SBIR Phase I'}

2024~275000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2415318.xml'}

NSF-MeitY: Strain Engineering of Magnetism in Ferrimagnetic Spinel Ferrites and Garnets by Combinatorial Substrate Epitaxy for Dual H- and E-Tunable High Frequency Devices

NSF

07/15/2024

06/30/2027

{'Value': 'Standard Grant'}

{'Code': '07010000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'ECCS', 'LongName': 'Div Of Electrical, Commun & Cyber Sys'}}

{'SignBlockName': 'Supriyo Bandyopadhyay', 'PO_EMAI': 'sbandyop@nsf.gov', 'PO_PHON': '7032925392'}

Title: Novel synthesis techniques for thin film magnetic oxides for electric and magnetic field tunable miniature high frequency devices <br/> <br/>Abstract<br/><br/>Ferrites and garnets are magnetic materials of choice for use in high frequency signal processing devices due to low loss characteristics. Their widespread use in frequency tunable devices, however, is limited by two factors: difficulties in miniaturization due to the need for a source of high external magnetic fields that will also require a large operating power. This international collaborative project is on novel synthesis techniques to tailor the properties of ferrite and garnet thin films to achieve a large built-in magnetic field to eliminate the need for high magnetic fields and power requirements and to design and fabricate voltage tunable devices by using a composite of magnetic and ferroelectric films. Magnetic oxide films will be grown on substrates with a variety of crystallographic orientations and characterized to identify the appropriate substrate orientation to achieve a large internal magnetic field. Following this critical step, ferrite and garnet films grown on desired substrates will be bonded to ferroelectric oxide films and the composites will be used in used in high frequency devices such as resonators and filters and tested in terms of voltage and magnetic field tunability and loss parameters. Anticipated key outcomes of this project are human resources development in materials and device technologies and a new family of smart, energy efficient, miniature high frequency devices for use in consumer electronics and communication systems.<br/><br/>This collaborative research program is aimed at tunable, miniature, planar devices with the use of (i) ferrite/garnet films with a self-magnetic bias provided by strain-induced anisotropy field and (ii) voltage tuning of the device facilitated by two different mechanisms: Non-Linear Magneto-electric Effects and linear magneto-electric coupling in a composite with a ferroelectric. The enhancement of the anisotropy field is to be achieved by introducing a controlled strain due to film-substrate lattice mismatch in the films grown by combinatorial substrate epitaxy, a technique suitable for simultaneous film growth on a polycrystalline substrate with a wide range of strain states, thereby enabling optimization of the substrate and material parameters for specific device applications. The most important task is the growth of yttrium iron garnet and nickel ferrite films by liquid phase epitaxy on polycrystalline substrates of yttrium aluminum garnet and magnesium aluminate with a large film-substrate lattice mismatch. Well-characterized substrates will be prepared by spark-plasma sintering and hot-pressing. Substrates and grown films will be characterized by electron and scanning probe microscopies. Localized ferromagnetic resonance measurements by scanning microwave microscopy will provide information on appropriate grain orientations for enhanced strain induced anisotropy fields. Films grown on single crystal substrates of preferred orientations will be bonded to ferroelectric lead zirconate titanate or lead magnesium niobate-lead titanate. Yttrium iron garnet-ferroelectric composites are to be used in 1-10 GHz resonators and band-pass and band-stop filters. Nickel ferrite-based composites are to be used for devices in the 10-20 GHz range and will be characterized in terms of broad-band tuning with a permanent magnet and narrow-band voltage tuning by magneto-electric effects and loss parameters and figures of merit. A partner in industry will evaluate their performance for use in 4G/5G wireless technologies and in similar high frequency communication systems.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

07/08/2024

07/08/2024

None

Grant

47.041

1

4900

4900

2415328

[{'FirstName': 'Gopalan', 'LastName': 'Srinivasan', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Gopalan Srinivasan', 'EmailAddress': 'srinivas@oakland.edu', 'NSF_ID': '000248608', 'StartDate': '07/08/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Hongwei', 'LastName': 'Qu', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Hongwei Qu', 'EmailAddress': 'qu2@oakland.edu', 'NSF_ID': '000510958', 'StartDate': '07/08/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]

{'Name': 'Oakland University', 'CityName': 'ROCHESTER', 'ZipCode': '483094401', 'PhoneNumber': '2483704116', 'StreetAddress': '2200 N SQUIRREL RD', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Michigan', 'StateCode': 'MI', 'CONGRESSDISTRICT': '11', 'CONGRESS_DISTRICT_ORG': 'MI11', 'ORG_UEI_NUM': 'HJTLACN81NK1', 'ORG_LGL_BUS_NAME': 'OAKLAND UNIVERSITY', 'ORG_PRNT_UEI_NUM': 'LY1HEB9XS5G8'}

{'Name': 'Oakland University', 'CityName': 'ROCHESTER', 'StateCode': 'MI', 'ZipCode': '483094401', 'StreetAddress': '2200 N SQUIRREL RD', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Michigan', 'CountryFlag': '1', 'CONGRESSDISTRICT': '11', 'CONGRESS_DISTRICT_PERF': 'MI11'}

{'Code': '151700', 'Text': 'EPMD-ElectrnPhoton&MagnDevices'}

2024~390001

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2415328.xml'}

SHF/FET: 2.5D/3D Heterogeneous Integration of In-Pixel and Near-Pixel Compute Chiplets

NSF

10/01/2024

09/30/2027

{'Value': 'Standard Grant'}

{'Code': '05010000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CCF', 'LongName': 'Division of Computing and Communication Foundations'}}

{'SignBlockName': 'Sankar Basu', 'PO_EMAI': 'sabasu@nsf.gov', 'PO_PHON': '7032927843'}

Personal computers and mobile phones have been the primary platforms for interaction with the digital world, pervading every corner of the modern society in the past few decades. Augmented Reality/Virtual Reality (AR/VR) is regarded as the general human-oriented computing platform for the next decade. In the smart headset, eye tracking provides crucial information on human perception, and it is a key pillar that supports many AR/VR applications such as displays, user interfaces, and foveated rendering. Hence, real-time processing of eye tracking workloads is critical, but modern eye tracking algorithms are much slower than the desired specifications (over an order of magnitude slower). Eye movements including saccade dynamics are one of the fastest movements in human body. Therefore, to accurately track eye movements, we need to perform image segmentation tasks at a very high frame rate (>1000 frames per second, FPS). However, this involves a large amount of data movement between the image sensor and the processor that performs the segmentation tasks. In the current practice, integration of frontend complementary-metal-oxide-semiconductor (CMOS) image sensor and backend microprocessor is slow and inefficient as they are generally placed in separate packages. To efficiently perform high frame rate processing, in-pixel and near-pixel compute paradigms have been proposed to reduce the latency and energy consumption from the costly data movements to provide >100× reduction in communication latency by placing compute close to the source of data. The outcome of this award will have synergies with other national efforts to revamp domestic semiconductor research and development under the CHIPS and Science Act. Besides the AR/VR applications, tracking fast eye movements could be useful in biomedical applications such as early diagnosis of Alzheimer’s and Parkinson’s diseases. The objective of the research and education integration is to train the next generation of workforce with domain expertise and interdisciplinary skills in the broad area of semiconductor device, integrated circuit and advanced packaging. <br/><br/>This award aims to advance the software-hardware co-design for in-pixel and near-pixel compute for eye tracking in AR/VR applications. A multi-mode image sensor that supports eye tracking is proposed, featuring a successive frame differencing method for the event map generation with in-pixel compute chiplet. It will be capable of providing both an event map at a higher frame rate as well as a full resolution image at a lower frame rate. Moreover, the near-pixel compute chiplet will run eye tracking inference with dual-mode deep neural networks for both high accuracy and high frame rate. The proposed research activities also include exploring the fundamental device technologies such as characterizing the amorphous oxide semiconductor transistor for pixel read-out circuitry and exploring the advanced packaging techniques for system-level heterogeneous integration. Silicon tape-outs are planned to validate the in-pixel and near-pixel compute chiplets with a pathway for heterogeneous integration on a silicon interposer.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

06/14/2024

06/14/2024

None

Grant

47.070

1

4900

4900

2415330

{'FirstName': 'Shimeng', 'LastName': 'Yu', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Shimeng Yu', 'EmailAddress': 'shimeng.yu@ece.gatech.edu', 'NSF_ID': '000656063', 'StartDate': '06/14/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Georgia Tech Research Corporation', 'CityName': 'ATLANTA', 'ZipCode': '303186395', 'PhoneNumber': '4048944819', 'StreetAddress': '926 DALNEY ST NW', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Georgia', 'StateCode': 'GA', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_ORG': 'GA05', 'ORG_UEI_NUM': 'EMW9FC8J3HN4', 'ORG_LGL_BUS_NAME': 'GEORGIA TECH RESEARCH CORP', 'ORG_PRNT_UEI_NUM': 'EMW9FC8J3HN4'}

{'Name': 'Georgia Tech Research Corporation', 'CityName': 'ATLANTA', 'StateCode': 'GA', 'ZipCode': '303320415', 'StreetAddress': '926 DALNEY ST NW', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Georgia', 'CountryFlag': '1', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_PERF': 'GA05'}

[{'Code': '089Y00', 'Text': 'FET-Fndtns of Emerging Tech'}, {'Code': '779800', 'Text': 'Software & Hardware Foundation'}]

2024~520000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2415330.xml'}

SBIR Phase II: Improved drug delivery platforms for localized and sustained drug deposition for traumatic injuries

NSF

08/15/2024

07/31/2026

{'Value': 'Cooperative Agreement'}

{'Code': '15030000', 'Directorate': {'Abbreviation': 'TIP', 'LongName': 'Dir for Tech, Innovation, & Partnerships'}, 'Division': {'Abbreviation': 'TI', 'LongName': 'Translational Impacts'}}

{'SignBlockName': 'Henry Ahn', 'PO_EMAI': 'hahn@nsf.gov', 'PO_PHON': '7032927069'}

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is the development of the safe and efficacious treatment for orthopedic and trauma surgery complications. This treatment includes localized and sustained drug delivery platform that will address the unmet medical needs for orthopedic patients. The successful commercialization of this technology is also expected to spur more nanomedicine and nanofabrication research for the medical field. The goal of the proposed project is to create a medication delivery system for soft tissue trauma consequences using sustained, biodegradable nanoparticles. The state of sustained-release technology will be greatly advanced, and the rehabilitation care provided to trauma patients will be substantially improved with this technology. The treatment to be developed will decrease the number of complications. New pharmacoeconomic research shows that cost/revenue over the long term is positively affected by fewer complications. Currently, there are major industry initiatives underway to create localized drug delivery systems for ophthalmic and cancer treatments. However, there are currently no approved or in-development treatments for this unmet medical need in orthopedic surgery. Support from the NSF will function as a spark to significantly increase the commercial effect of this first orthopedic nanomedicine project.<br/><br/>This Small Business Innovation Research (SBIR) Phase II project will address an innovative approach by utilizing anti-inflammatory nanoparticles embedded with potent Hedgehog pathway antagonist-Arsenic trioxide (NP102nano). This innovative and distinctive approach for developing a sustained-release, biodegradable drug delivery that delivers post-traumatic medication locally within the injured tissue is based on the desire to obviate unnecessary systemic drug applications and create a safe and effective off-the-shelf therapy. Such a product has the potential to improve outcomes for patients with post-traumatic injuries and reduce societal costs associated with additional surgeries and rehabilitation among trauma surgery patients. Current orthopedic treatments utilize systemic, untargeted administration of medications that result in unintended side effects, implant failure, and/or lack of intended efficacy. Moreover, the lack of an efficient delivery vehicle requires drug application at supraphysiological doses to reach clinical efficacy. The application at supraphysiological doses significantly increases the risk of side effects. It, therefore, is desirable to provide formulations and methods that target the delivery of medications only to the tissues needing treatment. This platform under development offers exactly this benefit. The goal of this project is to produce sufficient data for the pre-Investigational New Drug meeting with the regulatory authorities (such as Food and Drug Administration).<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/15/2024

08/15/2024

None

CoopAgrmnt

47.084

1

4900

4900

2415332

{'FirstName': 'EKATERINA', 'LastName': 'VERT-WONG', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'EKATERINA VERT-WONG', 'EmailAddress': 'katyav@nostopharma.com', 'NSF_ID': '000802882', 'StartDate': '08/15/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'NOSTOPHARMA, LLC', 'CityName': 'POTOMAC', 'ZipCode': '208543251', 'PhoneNumber': '2409975073', 'StreetAddress': '7600 CODDLE HARBOR LN', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Maryland', 'StateCode': 'MD', 'CONGRESSDISTRICT': '08', 'CONGRESS_DISTRICT_ORG': 'MD08', 'ORG_UEI_NUM': 'FKVPNPQK64H8', 'ORG_LGL_BUS_NAME': 'NOSTOPHARMA LLC', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'NOSTOPHARMA, LLC', 'CityName': 'POTOMAC', 'StateCode': 'MD', 'ZipCode': '208543251', 'StreetAddress': '7600 CODDLE HARBOR LN', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Maryland', 'CountryFlag': '1', 'CONGRESSDISTRICT': '08', 'CONGRESS_DISTRICT_PERF': 'MD08'}

{'Code': '537300', 'Text': 'SBIR Phase II'}

2024~1000000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2415332.xml'}

Scientists in the Family: Engaging Black Communities in STEM Through Accessible and Inclusive Science Stories

NSF

01/01/2025

12/31/2027

{'Value': 'Standard Grant'}

{'Code': '11090000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DRL', 'LongName': 'Division Of Research On Learning'}}

{'SignBlockName': 'Kevin A. Clark', 'PO_EMAI': 'kevclark@nsf.gov', 'PO_PHON': '7032928191'}

It is crucial for everyone to participate in the STEM enterprise to assure the continued technological and scientific advances. This project is unique because of its use of film and other visual assets to explore STEM identity, participation, and aspiration through a multigenerational approach featuring a Black mother, her family, and her community. The project consists of four components: a feature-length documentary, a community engagement experience (Scientists in the Family), a companion digital project (30 short-form videos), and an integrated research project. Family narratives and artifacts will be used to provide a window into the aspirations, challenges, and opportunities associated with choosing to participate in the STEM enterprise and their impact on individuals, families, and communities. This project is potentially transformative because it causes people to re-think how science is represented in individuals, their families, and their communities. It is important for all children and families to understand that historically underrepresented people have always been an integral part of science. Consistent with NSF’s pillar of accessibility and inclusivity and core values of diversity and inclusion, this project seeks to increase STEM engagement, curiosity, and belonging for multigenerational families historically underrepresented in STEM.<br/><br/>The project addresses the following research questions: 1) To what extent and how does participating in SiTF increase science center partners’ experience and confidence in engaging Black family members and integrating culturally relevant pedagogy into their STEM-based activities and community programming? 2) To what extent and how do Black families participate in the SiTF community engagement experiences, and is the envisioned “call and response” from screening to community events realized? 3) What is the impact of SiTF on participating youths’ interest, beliefs, and behavioral intent toward STEM and STEM-related careers? and 4) Does involvement in SiTF impact participating adult caregivers’ awareness of STEM opportunities and careers and their intention to encourage their children to further explore or pursue them? Audience outcomes are assessed through retrospective pre/post surveys, post screening and observational surveys, and creative artifacts. A culturally relevant theoretical framework is used to explore issues of STEM identity, belonging, and engagement by building knowledge through a two-part summative study consisting of cross-site and case study evaluations. By engaging students to discover their hidden scientist, the project will help underrepresented youth see themselves, their families, and communities as part of the STEM enterprise. This Type 5, Research in Support of Wide-reaching Public Engagement with STEM, project is funded by the Advancing Informal STEM Learning (AISL) program, which seeks to advance new approaches to, and evidence-based understanding of, the design and development of STEM learning in informal environments. This includes providing multiple pathways for broadening access to and engagement in STEM learning experiences.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

07/26/2024

07/30/2024

None

Grant

47.076

1

4900

4900

2415333

[{'FirstName': 'Priya', 'LastName': 'Mohabir', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Priya Mohabir', 'EmailAddress': 'pmohabir@nyscience.org', 'NSF_ID': '000621618', 'StartDate': '07/26/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Donald', 'LastName': 'Perry', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Donald Perry', 'EmailAddress': 'don@FamilyPicturesInstitute.org', 'NSF_ID': '000922143', 'StartDate': '07/26/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Thomas Allen', 'LastName': 'Harris', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Thomas Allen Harris', 'EmailAddress': 'thomas@familypicturesusa.com', 'NSF_ID': '000866234', 'StartDate': '07/26/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]

{'Name': 'New York Hall of Science', 'CityName': 'CORONA', 'ZipCode': '113682950', 'PhoneNumber': '7185959173', 'StreetAddress': '4701 111TH ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'New York', 'StateCode': 'NY', 'CONGRESSDISTRICT': '06', 'CONGRESS_DISTRICT_ORG': 'NY06', 'ORG_UEI_NUM': 'UQ7FBRE34HS5', 'ORG_LGL_BUS_NAME': 'NEW YORK HALL OF SCIENCE', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'New York Hall of Science', 'CityName': 'CORONA', 'StateCode': 'NY', 'ZipCode': '113682950', 'StreetAddress': '4701 111TH ST', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'New York', 'CountryFlag': '1', 'CONGRESSDISTRICT': '06', 'CONGRESS_DISTRICT_PERF': 'NY06'}

{'Code': '725900', 'Text': 'AISL'}

2024~3218776

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2415333.xml'}

Open Context: Sustaining a Collaborative Data Infrastructure for Archaeology

NSF

09/01/2024

08/31/2029

{'Value': 'Standard Grant'}

{'Code': '04040000', 'Directorate': {'Abbreviation': 'SBE', 'LongName': 'Direct For Social, Behav & Economic Scie'}, 'Division': {'Abbreviation': 'BCS', 'LongName': 'Division Of Behavioral and Cognitive Sci'}}

{'SignBlockName': 'John Yellen', 'PO_EMAI': 'jyellen@nsf.gov', 'PO_PHON': '7032928759'}

Data plays a key role in virtually every aspect of 21st century science. This project explores way of organizing and sharing archaeological research data to better address research questions about the human past, inform and educate the public, and align with ethical best practices. Open Context, launched in 2006, has emerged as a globally recognized platform for the review, curation, and publication of archaeological data documenting excavations, surveys, and collections research worldwide. With over two million records from 191 projects across 94 countries, including 173,000 images and illustrations, Open Context preserves invaluable archaeological contributions using open-source technologies and open standards. Data preservation is not merely a compliance issue; it involves significant ethical considerations, including cross-cultural intellectual property issues and conceptual challenges. Open Context places a strong emphasis on intellectual investment in data. It provides services that transform raw data into intelligible and useful information, ensuring their value and relevance to both scholars and the public. <br/><br/>Archaeological knowledge grows by synthesizing evidence accumulated over many years of field research by many investigators. Open Context helps make this vast body of material more accessible and useful. This project sustains and enhances Open Contexts's data curation services to enable scientific data to be reused with greater confidence and to meet evolving archaeological research needs. The investigators make technical improvements to increase the scalability and performance of Open Context’s infrastructure and support for services that promote greater scientific confidence in the provenance and authenticity of data. Open Context’s editorial team curate and publish groups of thematically related archaeological datasets that have a high reuse potential to support new research on topics as diverse as ancient trade and exchange systems and multi-disciplinary approaches to understanding human environment interactions. This work champions ethically and contextually appropriate approaches to open access and open data and addresses critical needs in the preservation of cultural heritage data. Open Context data curation contributions see increasing demand and impacts as computational methods continue to evolve, especially as interest in artificial intelligence grows. This initiative ensures the platform's continued impact in both scholarly and public spheres while advancing interdisciplinary collaboration and innovations to make scientific data more valued and beneficial to diverse communities.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

07/09/2024

07/09/2024

None

Grant

47.075

1

4900

4900

2415350

[{'FirstName': 'Eric', 'LastName': 'Kansa', 'PI_MID_INIT': 'C', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Eric C Kansa', 'EmailAddress': 'kansaeric@gmail.com', 'NSF_ID': '000452654', 'StartDate': '07/09/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Sarah', 'LastName': 'Kansa', 'PI_MID_INIT': 'W', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Sarah W Kansa', 'EmailAddress': 'sarahkansa@gmail.com', 'NSF_ID': '000553872', 'StartDate': '07/09/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}]

{'Name': 'The Alexandria Archive Institute', 'CityName': 'SAN FRANCISCO', 'ZipCode': '941272036', 'PhoneNumber': '4154257380', 'StreetAddress': '125 EL VERANO WAY', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'California', 'StateCode': 'CA', 'CONGRESSDISTRICT': '11', 'CONGRESS_DISTRICT_ORG': 'CA11', 'ORG_UEI_NUM': 'GJ2EJM2K5GD7', 'ORG_LGL_BUS_NAME': 'THE ALEXANDRIA ARCHIVE INSTITUTE', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'The Alexandria Archive Institute', 'CityName': 'SAN FRANCISCO', 'StateCode': 'CA', 'ZipCode': '941272036', 'StreetAddress': '125 EL VERANO WAY', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'California', 'CountryFlag': '1', 'CONGRESSDISTRICT': '11', 'CONGRESS_DISTRICT_PERF': 'CA11'}

{'Code': '139300', 'Text': 'ARCHAEOMETRY'}

2024~270834

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2415350.xml'}

University of Washington / R/V Thompson and R/V Rachel Carson - Oceanographic Instrumentation

NSF

06/01/2024

05/31/2026

{'Value': 'Standard Grant'}

{'Code': '06040100', 'Directorate': {'Abbreviation': 'GEO', 'LongName': 'Directorate For Geosciences'}, 'Division': {'Abbreviation': 'OCE', 'LongName': 'Division Of Ocean Sciences'}}

{'SignBlockName': 'George Voulgaris', 'PO_EMAI': 'gvoulgar@nsf.gov', 'PO_PHON': '7032927399'}

This award is for Oceanographic Instrumentation (OI) for R/V Thompson, a 274-foot general purpose, global class research vessel, and R/V Rachel Carson, a newly outfitted 72-foot coastal research vessel, both operated by the University of Washington (UW) as part of the U.S. Academic Research Fleet (ARF). UW will develop an underway CTD system and will acquire 2 CTD probes to be used with it. Also, UW seeks to install a 150 kHz Acoustic Doppler Current Profiler (ADCP) to complement the existing ADCP systems of different operational frequency; it will also purchase an additional Seabird SBE911plus sensor for use with the existing CTD rosette system.<br/><br/>The principal impact of the present proposal is under Merit Review Criterion 2 of the Proposal Guidelines (NSF 23-525). It provides infrastructure support for scientists to use the vessel and its shared-use instrumentation in support of their NSF-funded oceanographic research projects (which individually undergo separate review by the relevant research program of NSF). The acquisition, maintenance, and operation of shared-use instrumentation allows NSF-funded researchers from any US university or other organization access to well-maintained, high-quality, calibrated instruments for their research. It ensures the collection of high-quality oceanographic data in support of science, reduces the cost of that research, and expands the base of potential researchers.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

06/11/2024

06/11/2024

None

Grant

47.050

1

4900

4900

2415355

{'FirstName': 'Robert', 'LastName': 'Kamphaus', 'PI_MID_INIT': 'A', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Robert A Kamphaus', 'EmailAddress': 'kamphaus@uw.edu', 'NSF_ID': '000800132', 'StartDate': '06/11/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'University of Washington', 'CityName': 'SEATTLE', 'ZipCode': '981951016', 'PhoneNumber': '2065434043', 'StreetAddress': '4333 BROOKLYN AVE NE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Washington', 'StateCode': 'WA', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_ORG': 'WA07', 'ORG_UEI_NUM': 'HD1WMN6945W6', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF WASHINGTON', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'University of Washington', 'CityName': 'SEATTLE', 'StateCode': 'WA', 'ZipCode': '981951016', 'StreetAddress': '4333 BROOKLYN AVE NE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Washington', 'CountryFlag': '1', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_PERF': 'WA07'}

{'Code': '541300', 'Text': 'OCEANOGRAPHIC INSTRUMENTATION'}

2024~222536

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2415355.xml'}

Conference: Yamabe Memorial Symposium

NSF

08/01/2024

07/31/2025

{'Value': 'Standard Grant'}

{'Code': '03040000', 'Directorate': {'Abbreviation': 'MPS', 'LongName': 'Direct For Mathematical & Physical Scien'}, 'Division': {'Abbreviation': 'DMS', 'LongName': 'Division Of Mathematical Sciences'}}

{'SignBlockName': 'Qun Li', 'PO_EMAI': 'qli@nsf.gov', 'PO_PHON': '7032927465'}

The 2024 Yamabe Memorial Symposium will be held at the School of Mathematics of the University of Minnesota - Twin Cities, from Friday, October 4th to Sunday, October 6th, 2024. The Yamabe Memorial Symposium is a prestigious biennial conference in geometry and topology, established in 1962. It is renowned among geometers and topologists for its high-level, cutting-edge talks, strong support for U.S. graduate students, and its ability to connect leading experts with junior researchers through well-organized events. This year, the symposium will uphold this tradition, offering a comprehensive exploration of various aspects of symplectic and contact geometry in light of recent breakthroughs in these fields.<br/><br/>Recent major breakthroughs include advancements in the foundations of Floer theory, such as the development of stable homotopy theory for Floer theory, the introduction of global Kuranishi charts, and their applications to the Arnold conjecture over integers. Additionally, Floer theory has been applied to symplectic topology, including the refutation of the simplicity conjecture. Complementary to Floer theory, significant progress has been made in the study of Hamiltonian torus actions and topological methods in higher-dimensional contact structures. Eight confirmed speakers, comprising leading experts from around the world, will ensure comprehensive coverage of these areas. The webpage for the Yamabe Symposium is https://cse.umn.edu/math/yamabe-memorial-symposium<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

07/01/2024

07/01/2024

None

Grant

47.049

1

4900

4900

2415356

[{'FirstName': 'Michelle', 'LastName': 'Chu', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Michelle Chu', 'EmailAddress': 'mchu@umn.edu', 'NSF_ID': '000752689', 'StartDate': '07/01/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Erkao', 'LastName': 'Bao', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Erkao Bao', 'EmailAddress': 'bao@umn.edu', 'NSF_ID': '000864935', 'StartDate': '07/01/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}]

{'Name': 'University of Minnesota-Twin Cities', 'CityName': 'MINNEAPOLIS', 'ZipCode': '554552009', 'PhoneNumber': '6126245599', 'StreetAddress': '200 OAK ST SE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Minnesota', 'StateCode': 'MN', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_ORG': 'MN05', 'ORG_UEI_NUM': 'KABJZBBJ4B54', 'ORG_LGL_BUS_NAME': 'REGENTS OF THE UNIVERSITY OF MINNESOTA', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'University of Minnesota-Twin Cities', 'CityName': 'MINNEAPOLIS', 'StateCode': 'MN', 'ZipCode': '554552009', 'StreetAddress': '206 Church St. SE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Minnesota', 'CountryFlag': '1', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_PERF': 'MN05'}

{'Code': '126500', 'Text': 'GEOMETRIC ANALYSIS'}

2024~25000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2415356.xml'}

Conference: Shanks Workshop on Combinatorics and Graph Theory

NSF

04/01/2024

03/31/2025

{'Value': 'Standard Grant'}

{'Code': '03040000', 'Directorate': {'Abbreviation': 'MPS', 'LongName': 'Direct For Mathematical & Physical Scien'}, 'Division': {'Abbreviation': 'DMS', 'LongName': 'Division Of Mathematical Sciences'}}

{'SignBlockName': 'Stefaan De Winter', 'PO_EMAI': 'sgdewint@nsf.gov', 'PO_PHON': '7032922599'}

The “Shanks Workshop on Combinatorics and Graph Theory” will take place at Vanderbilt University, April 13-14, 2024. The focus of the workshop will be on structural graph theory, extremal combinatorics, graph coloring, Ramsey theory, and their intersections. The workshop will highlight significant recent achievements in these areas and provide a platform for researchers to share recent insights and tools, communicate their work, share open problems, and build new collaborations. The goals of the workshop are to (1) bring together researchers in combinatorics and graph theory to communicate and exchange ideas; (2) promote open problem-sharing and discussions among participants; (3) expose junior researchers to the latest developments in these areas; and (4) broaden and stimulate the research of junior, female, and underrepresented researchers.<br/><br/>The field of combinatorics concerns problems and techniques in discrete settings. It is closely related to other areas of mathematics and has many applications ranging from evolutionary biology to computer science and from logic to statistical physics. Graph theory is one of the oldest parts of combinatorics, and it has numerous natural connections to other areas. The workshop will feature two plenary speakers and eight early-career speakers. Moreover, we plan to organize an open problem session and a discussion session that allows participants of the workshop to exchange insights and ideas on open problems that are relevant and interesting to the larger mathematics and computer science community. The workshop website is located at https://my.vanderbilt.edu/cgt2024/.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

03/18/2024

03/18/2024

None

Grant

47.049

1

4900

4900

2415358

[{'FirstName': 'Mark', 'LastName': 'Ellingham', 'PI_MID_INIT': 'N', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Mark N Ellingham', 'EmailAddress': 'mark.ellingham@vanderbilt.edu', 'NSF_ID': '000348884', 'StartDate': '03/18/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Xiaonan', 'LastName': 'Liu', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Xiaonan Liu', 'EmailAddress': 'xiaonan.liu@vanderbilt.edu', 'NSF_ID': '000987027', 'StartDate': '03/18/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}]

{'Name': 'Vanderbilt University', 'CityName': 'NASHVILLE', 'ZipCode': '372032416', 'PhoneNumber': '6153222631', 'StreetAddress': '110 21ST AVE S', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Tennessee', 'StateCode': 'TN', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_ORG': 'TN05', 'ORG_UEI_NUM': 'GTNBNWXJ12D5', 'ORG_LGL_BUS_NAME': 'VANDERBILT UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Vanderbilt University', 'CityName': 'NASHVILLE', 'StateCode': 'TN', 'ZipCode': '372032416', 'StreetAddress': '110 21ST AVE S', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Tennessee', 'CountryFlag': '1', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_PERF': 'TN05'}

{'Code': '797000', 'Text': 'Combinatorics'}

2024~12800

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2415358.xml'}

Bridging Indigenous and Western Science to Build New, Placed-Based Approaches to Informal STEM Learning

NSF

09/01/2024

02/28/2026

{'Value': 'Standard Grant'}

{'Code': '11090000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DRL', 'LongName': 'Division Of Research On Learning'}}

{'SignBlockName': 'Robert Russell', 'PO_EMAI': 'rlrussel@nsf.gov', 'PO_PHON': '7032922995'}

Despite the interconnected nature of the world, traditional science disciplines, such as physics and biology, are often presented in isolation. Through a partnership between Aztec dancers and Western trained scientists, this partnership project seeks to bridge multiple knowledge systems to co-design and develop a clear pathway for Western and Indigenous knowledge to inform and generate new approaches to informal science education. Partnership activities are intentionally designed to support the effective integration of varied epistemologies, lived experiences, and perspectives by using a systems science approach. The project task force will facilitate the development of the partnership through a multi-day retreat, community dinners, and community-driven place-based experiences. <br/><br/>Partner collaboration will focus on the question, “How can multiple knowledge systems be considered to inform and transform community-driven, land-based science learning?” Project evaluation will document this science learning process and its outcomes to: (1) understand how this approach can strengthen change and strengthen a sense of belonging in STEM; and (2) identify the ways in which multiple knowledge systems and interconnections between knowledges and place/land emerge. The knowledge and partnership practices developed through this initiative will lay the foundation for expanding the partnership, generating new partnerships, and developing innovative, place-based informal STEM projects. The partnership will share knowledge and resources developed by the project via a blog, publications, and conference sessions.<br/><br/>This Partnership Development and Planning project is funded by the Advancing Informal STEM Learning (AISL) program, which seeks to advance new approaches to, and evidence-based understanding of, the design and development of STEM learning in informal environments. This includes providing multiple pathways for broadening access to and engagement in STEM learning experiences.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/25/2024

08/25/2024

None

Grant

47.076

1

4900

4900

2415369

[{'FirstName': 'Julie', 'LastName': 'Libarkin', 'PI_MID_INIT': 'C', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Julie C Libarkin', 'EmailAddress': 'libarkin@msu.edu', 'NSF_ID': '000476945', 'StartDate': '08/25/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Carolina', 'LastName': 'Michel', 'PI_MID_INIT': 'L', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Carolina L Michel', 'EmailAddress': 'Michelca@msu.edu', 'NSF_ID': '000967667', 'StartDate': '08/25/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}]

{'Name': 'Michigan State University', 'CityName': 'EAST LANSING', 'ZipCode': '488242600', 'PhoneNumber': '5173555040', 'StreetAddress': '426 AUDITORIUM RD RM 2', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Michigan', 'StateCode': 'MI', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_ORG': 'MI07', 'ORG_UEI_NUM': 'R28EKN92ZTZ9', 'ORG_LGL_BUS_NAME': 'MICHIGAN STATE UNIVERSITY', 'ORG_PRNT_UEI_NUM': 'VJKZC4D1JN36'}

{'Name': 'Michigan State University', 'CityName': 'EAST LANSING', 'StateCode': 'MI', 'ZipCode': '488242600', 'StreetAddress': '426 AUDITORIUM RD RM 2', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Michigan', 'CountryFlag': '1', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_PERF': 'MI07'}

{'Code': '725900', 'Text': 'AISL'}

2024~123847

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2415369.xml'}

NSF-meitY: Machine Learning Guided 3D Printing of Self-Healing Sustainable Concrete from Waste Materials

NSF

08/01/2024

07/31/2027

{'Value': 'Standard Grant'}

{'Code': '07020000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'CBET', 'LongName': 'Div Of Chem, Bioeng, Env, & Transp Sys'}}

{'SignBlockName': 'Bruce Hamilton', 'PO_EMAI': 'bhamilto@nsf.gov', 'PO_PHON': '7032920000'}

Concrete is the most common construction material used worldwide, with the primary constituent being ordinary Portland cement (OPC). Yet processing of OPC accounts for ~8% of human-caused global carbon emissions. Hence, reducing carbon emissions by designing sustainable concrete is a major goal of environmental and sustainability research. Countries across the globe have planned several steps to achieve carbon neutrality by the year 2050. The United Nations Environment Programme (UNEP) encourages the production of sustainable alternatives to decarbonize the construction sector. On the other hand, the disposal of household plastic waste is a significant challenge across the United States as well as across the globe. In the year 2018, about 35.7 million tons of plastic waste was produced in the United States. Hence, there is a need to develop an alternate strategy for repurposing plastic waste. Repurposing plastic waste and industrial waste for sustainable concrete development is well aligned environmental sustainability goals and this project is aimed in that direction. This project aims to not only enhance the scientific understanding and technological advancement of multifunctional sustainable concrete development using industrial and plastic waste with the help of 3D printing technology, and also is committed to training a diverse range of researchers and students.<br/><br/>The objective of this project is to fabricate 3D-printed sustainable self-healing concrete with multifunctional properties using industrial and household waste materials such as spent foundry sand and polyethylene terephthalate (PET) based plastic bottle waste and marine organisms, such as algae. The project aims to develop a novel machine-learning (ML)--based algorithm during 3D printing that is expected to introduce autonomy in the machine. The first objective is to fabricate the 3D-printed self-healing sustainable concrete followed by a durability assessment. The resultant physical and mechanical properties of the concrete will be predicted using numerical simulations followed by experimental validation. The second objective is dedicated to fabricating multilayered 3D-printed structures with silk protein waste and algae. The utilization of silk waste during 3D printing will introduce thermal insulation and algae will be useful to convert CO2 to O2 in the presence of sunlight. Finally, a novel real-time machine learning algorithm will be developed to introduce autonomy in the 3D-printing process. Successful completion of this project is expected to contribute to advancing scientific understanding of the underlying mechanisms of sustainable concrete development with autonomous 3D printing along with prototype development.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

07/10/2024

07/10/2024

None

Grant

47.041

1

4900

4900

2415385

[{'FirstName': 'David', 'LastName': 'Kaplan', 'PI_MID_INIT': 'L', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'David L Kaplan', 'EmailAddress': 'david.kaplan@tufts.edu', 'NSF_ID': '000162550', 'StartDate': '07/10/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Markus', 'LastName': 'Buehler', 'PI_MID_INIT': 'J', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Markus J Buehler', 'EmailAddress': 'mbuehler@MIT.EDU', 'NSF_ID': '000326937', 'StartDate': '07/10/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Arjak', 'LastName': 'Bhattacharjee', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Arjak Bhattacharjee', 'EmailAddress': 'arjak.bhattacharjee@nmt.edu', 'NSF_ID': '000990563', 'StartDate': '07/10/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}]

{'Name': 'New Mexico Institute of Mining and Technology', 'CityName': 'SOCORRO', 'ZipCode': '878014681', 'PhoneNumber': '5758355496', 'StreetAddress': '801 LEROY PL', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'New Mexico', 'StateCode': 'NM', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_ORG': 'NM02', 'ORG_UEI_NUM': 'HZJ2JZUALWN4', 'ORG_LGL_BUS_NAME': 'NEW MEXICO INSTITUTE OF MINING AND TECHNOLOGY', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'New Mexico Institute of Mining and Technology', 'CityName': 'SOCORRO', 'StateCode': 'NM', 'ZipCode': '878014681', 'StreetAddress': '801 LEROY PL', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'New Mexico', 'CountryFlag': '1', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_PERF': 'NM02'}

{'Code': '764300', 'Text': 'EnvS-Environmtl Sustainability'}

2024~499999

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2415385.xml'}

From Stories to Solutions: Engaging Latinx Families as Design Partners to Advance Equitable Informal Engineering Learning Opportunities for Young Children

NSF

09/01/2024

08/31/2027

{'Value': 'Standard Grant'}

{'Code': '11090000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DRL', 'LongName': 'Division Of Research On Learning'}}

{'SignBlockName': 'Alicia Santiago Gonzalez', 'PO_EMAI': 'asantiag@nsf.gov', 'PO_PHON': '7032924546'}

Many point to the potentially transformative role early engineering education can play in broadening participation in STEM among individuals from culturally and linguistically diverse communities. Moreover, this idea has driven the dramatic expansion of tinkering and making spaces and programs that provide engineering learning opportunities for children and their families in the early years. To fully unlock the promise of these kinds of early learning opportunities for advancing equity in engineering, however, it is necessary to do more than increase access. This project addresses the further need to understand how to design these engineering activities and programs to connect with and build upon cultural and familial strengths and practices for supporting children's learning. The project takes as a starting point that many families, and particularly those from cultural communities with rich oral storytelling traditions such as families of Latin American heritages, rely frequently on oral storytelling to communicate knowledge to young children. The project focuses on how Latinx families' everyday practices around engineering and oral storytelling can form the basis for the design of new engineering learning opportunities that recognize and value the assets of individuals and communities. An emphasis on why and how oral storytelling can underpin promising engineering educational practices is in keeping with efforts to engage cultural and familial resources for STEM learning, as well as work in developmental psychology and learning sciences demonstrating that oral stories offer powerful mechanisms for constructing knowledge and making memorable learning. Sharing stories in the context of engineering activities may also foster a sense of belonging, for example, by highlighting the human side of engineering and how it can help others and make things better.<br/><br/>The project reflects a collaboration among community leaders at Palenque LSNA, educators at Chicago Children’s Museum (CCM), and researchers at Loyola University Chicago. With a community-engaged process and design-based research methods, 90 Latinx caregivers and their 5- to 8-year-old children will participate as design partners to create playful, hands-on early engineering activities that are relatable and meaningful. Palenque and CCM facilitators will explore strategies for centering oral storytelling as a potentially powerful tool for empowering family design partners. In turn, the resulting activities from the co-design sessions will form community-based informal engineering programs offered to more than 100 community members annually, and during summertime family programming at the museum when the number of visitors can exceed 200 per day. In the community- and museum-based programs, the project will research whether and to what extent the co-designed programs impact family engineering learning in community- and museum-based settings. Additionally, the project will identify practices for effectively sharing the co-design process and first-person voices of family co-design partners, and study how doing so might impact the engineering engagement and stories of connection and belonging expressed by other families participating in the programs. The project will yield a design narrative and a toolkit of resources reflecting what is learned about co-creating engineering learning opportunities for and with community members in ways that reflect families' cultural resources and everyday practices. The project will also contribute practices that support other families in community- and museum-based programs to connect their own stories to hands-on engineering activities in ways that can advance engineering engagement and expressions of belonging. The work will provide robust training and professional development opportunities across the three-way institutional partnership. Practice resources and other products of the work will be created collaboratively and disseminated broadly with contributions of all involved acknowledged. This Integrating Research and Practice collaborative project is funded by the Advancing Informal STEM Learning (AISL) program, which seeks to advance new approaches to, and evidence-based understanding of, the design and development of STEM learning in informal environments. This includes providing multiple pathways for broadening access to and engagement in STEM learning experiences.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/07/2024

08/07/2024

None

Grant

47.076

1

4900

4900

2415398

{'FirstName': 'Catherine', 'LastName': 'Haden', 'PI_MID_INIT': 'A', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Catherine A Haden', 'EmailAddress': 'chaden@luc.edu', 'NSF_ID': '000193082', 'StartDate': '08/07/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Loyola University of Chicago', 'CityName': 'CHICAGO', 'ZipCode': '606112147', 'PhoneNumber': '7735082471', 'StreetAddress': '820 N MICHIGAN AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Illinois', 'StateCode': 'IL', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_ORG': 'IL05', 'ORG_UEI_NUM': 'CVNBL4GDUKF3', 'ORG_LGL_BUS_NAME': 'LOYOLA UNIVERSITY OF CHICAGO', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Loyola University of Chicago', 'CityName': 'CHICAGO', 'StateCode': 'IL', 'ZipCode': '606112147', 'StreetAddress': '820 N MICHIGAN AVE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Illinois', 'CountryFlag': '1', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_PERF': 'IL05'}

{'Code': '725900', 'Text': 'AISL'}

2024~733043

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2415398.xml'}

Collaborative Research: From Stories to Solutions: Engaging Latinx Families as Design Partners to Advance Equitable Informal Engineering Learning Opportunities for Young Children

NSF

09/01/2024

08/31/2027

{'Value': 'Standard Grant'}

{'Code': '11090000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DRL', 'LongName': 'Division Of Research On Learning'}}

{'SignBlockName': 'Alicia Santiago Gonzalez', 'PO_EMAI': 'asantiag@nsf.gov', 'PO_PHON': '7032924546'}

Many point to the potentially transformative role early engineering education can play in broadening participation in STEM among individuals from culturally and linguistically diverse communities. Moreover, this idea has driven the dramatic expansion of tinkering and making spaces and programs that provide engineering learning opportunities for children and their families in the early years. To fully unlock the promise of these kinds of early learning opportunities for advancing equity in engineering, however, it is necessary to do more than increase access. This project addresses the further need to understand how to design these engineering activities and programs to connect with and build upon cultural and familial strengths and practices for supporting children's learning. The project takes as a starting point that many families, and particularly those from cultural communities with rich oral storytelling traditions such as families of Latin American heritages, rely frequently on oral storytelling to communicate knowledge to young children. The project focuses on how Latinx families' everyday practices around engineering and oral storytelling can form the basis for the design of new engineering learning opportunities that recognize and value the assets of individuals and communities. An emphasis on why and how oral storytelling can underpin promising engineering educational practices is in keeping with efforts to engage cultural and familial resources for STEM learning, as well as work in developmental psychology and learning sciences demonstrating that oral stories offer powerful mechanisms for constructing knowledge and making memorable learning. Sharing stories in the context of engineering activities may also foster a sense of belonging, for example, by highlighting the human side of engineering and how it can help others and make things better.<br/><br/>The project reflects a collaboration among community leaders at Palenque LSNA, educators at Chicago Children’s Museum (CCM), and researchers at Loyola University Chicago. With a community-engaged process and design-based research methods, 90 Latinx caregivers and their 5- to 8-year-old children will participate as design partners to create playful, hands-on early engineering activities that are relatable and meaningful. Palenque and CCM facilitators will explore strategies for centering oral storytelling as a potentially powerful tool for empowering family design partners. In turn, the resulting activities from the co-design sessions will form community-based informal engineering programs offered to more than 100 community members annually, and during summertime family programming at the museum when the number of visitors can exceed 200 per day. In the community- and museum-based programs, the project will research whether and to what extent the co-designed programs impact family engineering learning in community- and museum-based settings. Additionally, the project will identify practices for effectively sharing the co-design process and first-person voices of family co-design partners, and study how doing so might impact the engineering engagement and stories of connection and belonging expressed by other families participating in the programs. The project will yield a design narrative and a toolkit of resources reflecting what is learned about co-creating engineering learning opportunities for and with community members in ways that reflect families' cultural resources and everyday practices. The project will also contribute practices that support other families in community- and museum-based programs to connect their own stories to hands-on engineering activities in ways that can advance engineering engagement and expressions of belonging. The work will provide robust training and professional development opportunities across the three-way institutional partnership. Practice resources and other products of the work will be created collaboratively and disseminated broadly with contributions of all involved acknowledged. This Integrating Research and Practice collaborative project is funded by the Advancing Informal STEM Learning (AISL) program, which seeks to advance new approaches to, and evidence-based understanding of, the design and development of STEM learning in informal environments. This includes providing multiple pathways for broadening access to and engagement in STEM learning experiences.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/07/2024

08/07/2024

None

Grant

47.076

1

4900

4900

2415399

[{'FirstName': 'Kim', 'LastName': 'Koin', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Kim Koin', 'EmailAddress': 'kimk@chicagochildrensmuseum.org', 'NSF_ID': '000791965', 'StartDate': '08/07/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Natalie', 'LastName': 'Bortoli', 'PI_MID_INIT': 'A', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Natalie A Bortoli', 'EmailAddress': 'natalieb@chicagochildrensmuseum.org', 'NSF_ID': '000792000', 'StartDate': '08/07/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Silvia', 'LastName': 'Gonzalez', 'PI_MID_INIT': 'J', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Silvia J Gonzalez', 'EmailAddress': 'sgonzalez@palenquelsna.org', 'NSF_ID': '000992352', 'StartDate': '08/07/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Norma', 'LastName': 'Rios Sierra', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Norma Rios Sierra', 'EmailAddress': 'Nrios@palenquelsna.org', 'NSF_ID': '000992243', 'StartDate': '08/07/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]

{'Name': "Chicago Children's Museum", 'CityName': 'CHICAGO', 'ZipCode': '606113580', 'PhoneNumber': '3124647717', 'StreetAddress': '700 E GRAND AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Illinois', 'StateCode': 'IL', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_ORG': 'IL05', 'ORG_UEI_NUM': 'ZJV1AL1FPMR9', 'ORG_LGL_BUS_NAME': 'CHICAGO CHILDRENS MUSEUM', 'ORG_PRNT_UEI_NUM': 'ZJV1AL1FPMR9'}

{'Name': "Chicago Children's Museum", 'CityName': 'CHICAGO', 'StateCode': 'IL', 'ZipCode': '606113580', 'StreetAddress': '700 E GRAND AVE # 127', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Illinois', 'CountryFlag': '1', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_PERF': 'IL05'}

{'Code': '725900', 'Text': 'AISL'}

2024~787042

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2415399.xml'}

CAREER: Towards Practical Systems for Trustworthy Cloud Computing

NSF

10/01/2023

08/31/2025

{'Value': 'Continuing Grant'}

{'Code': '05050000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CNS', 'LongName': 'Division Of Computer and Network Systems'}}

{'SignBlockName': 'Karen Karavanic', 'PO_EMAI': 'kkaravan@nsf.gov', 'PO_PHON': '7032922594'}

An increasing number of individuals, enterprises, and governments <br/>migrate their data and applications to the cloud. Computations delegated <br/>to the cloud may return erroneous results, outsourced files may be lost <br/>or discarded, and sensitive information may be arbitrarily accessed for <br/>advertising purposes. This project enhances the ability of cloud companies <br/>to integrate advanced protection mechanisms into their products, benefiting <br/>the online safety of cloud clients. The project also aims to improve security <br/>education via new undergraduate and graduate curriculum and outreach to high school<br/>students.<br/><br/>This project addresses foundational problems on the security, availability, and <br/>privacy of cloud computing by using an application-driven approach and demonstrates <br/>the broad applicability of this theory in practice. The project develops low bandwidth and<br/>sub-linear computation protocols for securely recovering correct data blocks and computation <br/>results. The researchers investigate practical and expressive privacy preserving algorithms<br/>with reduced leakage profiles and low I/O complexity for advanced queries on encrypted <br/>static and dynamic data. They also develop new fundamental techniques for verifying <br/>frequently recurrent classes of delegated computations<br/>

03/08/2024

05/24/2024

None

Grant

47.070

1

4900

4900

2415403

{'FirstName': 'Charalampos', 'LastName': 'Papamanthou', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Charalampos Papamanthou', 'EmailAddress': 'cpap@umd.edu', 'NSF_ID': '000654890', 'StartDate': '03/08/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Yale University', 'CityName': 'NEW HAVEN', 'ZipCode': '065113572', 'PhoneNumber': '2037854689', 'StreetAddress': '150 MUNSON ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Connecticut', 'StateCode': 'CT', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_ORG': 'CT03', 'ORG_UEI_NUM': 'FL6GV84CKN57', 'ORG_LGL_BUS_NAME': 'YALE UNIV', 'ORG_PRNT_UEI_NUM': 'FL6GV84CKN57'}

{'Name': 'YALE UNIVERSITY', 'CityName': 'NEW HAVEN', 'StateCode': 'CT', 'ZipCode': '065118917', 'StreetAddress': '105 WALL ST', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Connecticut', 'CountryFlag': '1', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_PERF': 'CT03'}

{'Code': '806000', 'Text': 'Secure &Trustworthy Cyberspace'}

['2020~23089', '2021~100569']

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2415403.xml'}

Collaborative Research: A study of the collective dynamics of multiple flagella in a bacterial bundle

NSF

07/01/2024

06/30/2027

{'Value': 'Standard Grant'}

{'Code': '07020000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'CBET', 'LongName': 'Div Of Chem, Bioeng, Env, & Transp Sys'}}

{'SignBlockName': 'Ron Joslin', 'PO_EMAI': 'rjoslin@nsf.gov', 'PO_PHON': '7032927030'}

The ability of bacteria to swim in fluid media is critical for their survival and proliferation in diverse environments and plays a crucial role in many important natural, environmental and bioengineering processes. As one of the most common types of bacteria, peritrichous bacteria such as Escherichia coli swim by rotating a single helical bundle, which is formed from multiple flagellar filaments growing all over the bacterial body. This proposal addresses a fundamental question in the fluid dynamics of the swimming of peritrichous bacteria, i.e., how do the multiple flagellar filaments of a bacterium synchronize and rotate collectively to provide a coherent thrust, enabling the swimming of the bacterium? Toward solving this long-standing problem, the project will integrate experiments on macroscopic model flagella with experiments on microscopic living bacteria and state-of-the-art numerical simulations. Through a systematic and iterative approach, the project aims to resolve the underlying fluid-mechanics principles governing the complex dynamics of bacterial flagellar bundles and uncover their effects on bacterial swimming. The project will provide good opportunities for recruiting undergraduate students from a minority-serving college in frontier research and for designing scientific demonstrations on bacterial swimming for outreach activities. <br/><br/>The goal of this project is to understand the synchronization and collective dynamics of multiple flagella in a bacterial bundle. Particularly, the project aims to reveal how multiple flagella synchronize to form a functioning bundle – an indispensable process for the swimming and chemotaxis of a large class of bacteria – and illustrate the collective dynamics of flagella in the bundle. More specifically, the project will construct the most accurate scale experiments to date with previously unexplored features, which will provide a benchmark to develop an immersed-boundary numerical model for simulating flagellar dynamics at different scales. The predictions of both the scale experiments and numerical simulations will be finally compared with microscopic experiments on real bacteria. More broadly, the work will shed light onto the origin of hydrodynamic synchronization and facilitate the development of engineering techniques for tailoring the synchronized dynamics of micron-sized objects. Beyond the specific scientific and engineering questions, the project will expand the limited toolbox to tackle challenging issues associated with low-Reynolds-number fluid-structure interactions. A versatile experimental platform and a quantitative numerical model will be delivered to the research community.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

07/10/2024

07/10/2024

None

Grant

47.041

1

4900

4900

2415405

{'FirstName': 'Xiang', 'LastName': 'Cheng', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Xiang Cheng', 'EmailAddress': 'xcheng@umn.edu', 'NSF_ID': '000654312', 'StartDate': '07/10/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'University of Minnesota-Twin Cities', 'CityName': 'MINNEAPOLIS', 'ZipCode': '554552009', 'PhoneNumber': '6126245599', 'StreetAddress': '200 OAK ST SE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Minnesota', 'StateCode': 'MN', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_ORG': 'MN05', 'ORG_UEI_NUM': 'KABJZBBJ4B54', 'ORG_LGL_BUS_NAME': 'REGENTS OF THE UNIVERSITY OF MINNESOTA', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'University of Minnesota-Twin Cities', 'CityName': 'MINNEAPOLIS', 'StateCode': 'MN', 'ZipCode': '554552009', 'StreetAddress': '200 OAK ST SE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Minnesota', 'CountryFlag': '1', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_PERF': 'MN05'}

{'Code': '144300', 'Text': 'FD-Fluid Dynamics'}

2024~354066

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2415405.xml'}

Collaborative Research: A study of the collective dynamics of multiple flagella in a bacterial bundle

NSF

07/01/2024

06/30/2027

{'Value': 'Standard Grant'}

{'Code': '07020000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'CBET', 'LongName': 'Div Of Chem, Bioeng, Env, & Transp Sys'}}

{'SignBlockName': 'Ron Joslin', 'PO_EMAI': 'rjoslin@nsf.gov', 'PO_PHON': '7032927030'}

The ability of bacteria to swim in fluid media is critical for their survival and proliferation in diverse environments and plays a crucial role in many important natural, environmental and bioengineering processes. As one of the most common types of bacteria, peritrichous bacteria such as Escherichia coli swim by rotating a single helical bundle, which is formed from multiple flagellar filaments growing all over the bacterial body. This proposal addresses a fundamental question in the fluid dynamics of the swimming of peritrichous bacteria, i.e., how do the multiple flagellar filaments of a bacterium synchronize and rotate collectively to provide a coherent thrust, enabling the swimming of the bacterium? Toward solving this long-standing problem, the project will integrate experiments on macroscopic model flagella with experiments on microscopic living bacteria and state-of-the-art numerical simulations. Through a systematic and iterative approach, the project aims to resolve the underlying fluid-mechanics principles governing the complex dynamics of bacterial flagellar bundles and uncover their effects on bacterial swimming. The project will provide good opportunities for recruiting undergraduate students from a minority-serving college in frontier research and for designing scientific demonstrations on bacterial swimming for outreach activities. <br/><br/>The goal of this project is to understand the synchronization and collective dynamics of multiple flagella in a bacterial bundle. Particularly, the project aims to reveal how multiple flagella synchronize to form a functioning bundle – an indispensable process for the swimming and chemotaxis of a large class of bacteria – and illustrate the collective dynamics of flagella in the bundle. More specifically, the project will construct the most accurate scale experiments to date with previously unexplored features, which will provide a benchmark to develop an immersed-boundary numerical model for simulating flagellar dynamics at different scales. The predictions of both the scale experiments and numerical simulations will be finally compared with microscopic experiments on real bacteria. More broadly, the work will shed light onto the origin of hydrodynamic synchronization and facilitate the development of engineering techniques for tailoring the synchronized dynamics of micron-sized objects. Beyond the specific scientific and engineering questions, the project will expand the limited toolbox to tackle challenging issues associated with low-Reynolds-number fluid-structure interactions. A versatile experimental platform and a quantitative numerical model will be delivered to the research community.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

07/10/2024

07/10/2024

None

Grant

47.041

1

4900

4900

2415406

{'FirstName': 'Sookkyung', 'LastName': 'Lim', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Sookkyung Lim', 'EmailAddress': 'sookkyung.lim@uc.edu', 'NSF_ID': '000174558', 'StartDate': '07/10/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'University of Cincinnati Main Campus', 'CityName': 'CINCINNATI', 'ZipCode': '452202872', 'PhoneNumber': '5135564358', 'StreetAddress': '2600 CLIFTON AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Ohio', 'StateCode': 'OH', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_ORG': 'OH01', 'ORG_UEI_NUM': 'DZ4YCZ3QSPR5', 'ORG_LGL_BUS_NAME': 'CINCINNATI UNIV OF', 'ORG_PRNT_UEI_NUM': 'DZ4YCZ3QSPR5'}

{'Name': 'University of Cincinnati Main Campus', 'CityName': 'CINCINNATI', 'StateCode': 'OH', 'ZipCode': '452202872', 'StreetAddress': '2600 CLIFTON AVE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Ohio', 'CountryFlag': '1', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_PERF': 'OH01'}

{'Code': '144300', 'Text': 'FD-Fluid Dynamics'}

2024~195656

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2415406.xml'}

Promoting Computational Thinking and STEM Attitudes for Individuals with Disabilities Using Game Builder Garage

NSF

08/15/2024

07/31/2027

{'Value': 'Continuing Grant'}

{'Code': '11090000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DRL', 'LongName': 'Division Of Research On Learning'}}

{'SignBlockName': 'Kevin A. Clark', 'PO_EMAI': 'kevclark@nsf.gov', 'PO_PHON': '7032928191'}

It is essential to foster diversity, equity, and inclusion by making programs more accessible for individuals with disabilities to broaden the STEM enterprise and create a more inclusive workforce. Despite rising awareness of barriers in STEM for those with disabilities most efforts have centered on physical disabilities, often overlooking neurodiverse learners. To address the issues of neurodiverse learners, this project leverages game development innovations to offer an engaging STEM curriculum tailored for individuals with disabilities through video game design. The focus is on designing a curriculum to support the development of computational thinking skills with middle-school students with disabilities to: (1) embed acquisition of computational concepts and practices within a highly engaging context; (2) complement the increasingly computational nature of STEM careers; and (3) lead to tangible representations of learning. The design, development, implementation, and evaluation of an accessible video game design curriculum using Nintendo’s Game Builder Garage platform will be deployed in informal STEM environments to investigate how participation influences computational thinking skills and attitudes towards STEM for individuals with disabilities. <br/><br/>The aims of this project are to influence STEM perceptions and skills for individuals with disabilities in informal STEM learning settings. The target audience are middle school students with disabilities. This Integrating Research and Practice project will be guided by these research questions: 1) How can a curriculum be designed to support development of computational thinking for individuals with disabilities for deployment in informal STEM learning environments? 2) How do stakeholders (e.g., individuals with disabilities, caregivers, experts) perceive the accessibility and ease-of-use of the curriculum and game development tools, and what improvements are needed? 3) What is the influence of the Gaming for Good learning experience on participants’ perceptions towards STEM? 4) What is the influence of the Gaming for Good learning experience on participants’ computational thinking skills? A mixed methods research design and an iterative learning experience design evaluation approach, which includes formative, summative, and remedial phases, will be employed in this project. As a result, this project will produce a co-designed inclusive digital game-based learning curriculum that addresses the following STEM topics: data, modeling & simulation, computational problem solving, and systems thinking. The broader impact of this project is that by shifting from a programming to a data focus in game making, STEM careers like computer science, game design, and instructional design will be more accessible to individuals with disabilities. <br/><br/>This project is funded by the Advancing Informal STEM Learning (AISL) program, which seeks to advance new approaches to, and evidence-based understanding of, the design and development of STEM learning in informal environments. This includes providing multiple pathways for broadening access to and engagement in STEM learning experiences.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/06/2024

08/06/2024

None

Grant

47.076

1

4900

4900

2415415

[{'FirstName': 'Amanda', 'LastName': 'Olsen', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Amanda Olsen', 'EmailAddress': 'aolsen@missouri.edu', 'NSF_ID': '000833183', 'StartDate': '08/06/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Noah', 'LastName': 'Glaser', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Noah Glaser', 'EmailAddress': 'noah.glaser@missouri.edu', 'NSF_ID': '000871086', 'StartDate': '08/06/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Matthew', 'LastName': 'Schmidt', 'PI_MID_INIT': 'M', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Matthew M Schmidt', 'EmailAddress': 'matthew.schmidt@uga.edu', 'NSF_ID': '000867632', 'StartDate': '08/06/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Lucas', 'LastName': 'Jensen', 'PI_MID_INIT': 'J', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Lucas J Jensen', 'EmailAddress': 'ljensen@georgiasouthern.edu', 'NSF_ID': '000867193', 'StartDate': '08/06/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Kieren', 'LastName': 'Mendoza', 'PI_MID_INIT': 'R', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Kieren R Mendoza', 'EmailAddress': 'krende@unomaha.edu', 'NSF_ID': '000907828', 'StartDate': '08/06/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]

{'Name': 'University of Missouri-Columbia', 'CityName': 'COLUMBIA', 'ZipCode': '652113020', 'PhoneNumber': '5738827560', 'StreetAddress': '121 UNIVERSITY HALL', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Missouri', 'StateCode': 'MO', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_ORG': 'MO03', 'ORG_UEI_NUM': 'SZPJL5ZRCLF4', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF MISSOURI SYSTEM', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'University of Missouri-Columbia', 'CityName': 'COLUMBIA', 'StateCode': 'MO', 'ZipCode': '652113020', 'StreetAddress': '121 UNIVERSITY HALL', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Missouri', 'CountryFlag': '1', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_PERF': 'MO03'}

{'Code': '725900', 'Text': 'AISL'}

2024~1099362

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2415415.xml'}

CAREER: Coding Subspaces: Error Correction, Compression and Applications

NSF

01/01/2024

04/30/2025

{'Value': 'Continuing Grant'}

{'Code': '05010000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CCF', 'LongName': 'Division of Computing and Communication Foundations'}}

{'SignBlockName': 'Phillip Regalia', 'PO_EMAI': 'pregalia@nsf.gov', 'PO_PHON': '7032922981'}

In today’s technological world, an enormous amount of data is being constantly generated, transmitted, received, processed, and stored at an unprecedented scale. The classical approach of representing data as blocks of information bits falls short of addressing diverse requirements, including scalability, efficiency, and reliability, of the next generation storage, computation, and communication systems. This project develops an alternative paradigm for transmission of data across massively connected wireless networks by proposing methods to embed the information into mathematical constructs called subspaces (i.e., linear-algebraic objects in a vector space), via a technique called subspace coding. While these structures capture the essence of gathered data in a wide range of signal processing applications, fundamental limits of compression as well as practical and universal techniques to attain these limits are not understood. This project characterizes a natural duality between error correction and compression in the subspace domain and proposes to leverage this connection in order to develop explicit and efficient compression mechanisms for massive data sets that exhibit certain properties. This interdisciplinary project is tied with an education plan and provides a stimulating and innovative research environment for students at all levels. Furthermore, workshops are developed as part of an active outreach program in order to introduce high school students to concepts in fields related to data science and communications, exposing them to careers essential to tomorrow’s workforce.<br/><br/>Wireless networks are rapidly growing in size, are becoming more hierarchical, and are becoming increasingly distributed. Conventional methods including channel estimation of point-to-point links and block coding do not properly scale with the size of such massive networks. This project proposes that subspace coding in the analog domain becomes relevant for conveying information across networks in such a scenario. Furthermore, the dual problem in the compression domain is central to a wide range of applications involving large-scale raw data, often exhibiting low-dimensional structures, which require techniques for low-dimensional subspace recovery and dimensionality reduction. The specific objectives of this project are summarized as follows: (1) Provide a comprehensive framework, including a certain metric space and an analog operator channel, to study coding for wireless networks in a non-coherent fashion; (2) Construct subspace codes for analog operator channels and characterize their performance; (3) Develop techniques for low-rank subspace recovery given constrained observations; (4) Characterize fundamental limits on compression of low-rank matrices and leverage the duality with subspace codes to design explicit compression mechanisms; (5) Develop schemes for subspace-coded distributed computation to efficiently compute the outcome of algorithms operating over matrices and subspaces while minimizing the delay.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

02/05/2024

06/10/2024

None

Grant

47.070

1

4900

4900

2415440

{'FirstName': 'Hessam', 'LastName': 'Mahdavifar', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Hessam Mahdavifar', 'EmailAddress': 'h.mahdavifar@northeastern.edu', 'NSF_ID': '000743600', 'StartDate': '02/05/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Northeastern University', 'CityName': 'BOSTON', 'ZipCode': '021155005', 'PhoneNumber': '6173733004', 'StreetAddress': '360 HUNTINGTON AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Massachusetts', 'StateCode': 'MA', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_ORG': 'MA07', 'ORG_UEI_NUM': 'HLTMVS2JZBS6', 'ORG_LGL_BUS_NAME': 'NORTHEASTERN UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Northeastern University', 'CityName': 'BOSTON', 'StateCode': 'MA', 'ZipCode': '021155005', 'StreetAddress': '360 HUNTINGTON AVE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Massachusetts', 'CountryFlag': '1', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_PERF': 'MA07'}

{'Code': '779700', 'Text': 'Comm & Information Foundations'}

['2021~335284', '2024~131951']

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2415440.xml'}

CAREER: Machine learning, Mapping Spaces, and Obstruction Theoretic Methods in Topological Data Analysis

NSF

04/01/2024

04/30/2025

{'Value': 'Continuing Grant'}

{'Code': '03040000', 'Directorate': {'Abbreviation': 'MPS', 'LongName': 'Direct For Mathematical & Physical Scien'}, 'Division': {'Abbreviation': 'DMS', 'LongName': 'Division Of Mathematical Sciences'}}

{'SignBlockName': 'Jodi Mead', 'PO_EMAI': 'jmead@nsf.gov', 'PO_PHON': '7032927212'}

Data analysis can be described as the dual process of extracting information from observations, and of understanding patterns in a principled manner. This process and the deployment of data-centric technologies have recently brought unprecedented advances in many scientific fields, as well as increased global prosperity with the advent of knowledge-based economies and systems. At a high level, this revolution is driven by two thrusts: the modern technologies which allow for the collection of complex data sets, and the theories and algorithms we use to make sense of them. That said, and for all its benefits, extracting actionable knowledge from data is difficult. Observations gathered in uncontrolled environments are often high-dimensional, complex and noisy; and even when controlled experiments are used, the intricate systems that underlie them --- like those from meteorology, chemistry, medicine and biology --- can yield data sets with highly nontrivial underlying topology. This refers to properties such as the number of disconnected pieces (i.e., clusters), the existence of holes or the orientability of the data space. The research funded through this CAREER award will leverage ideas from algebraic topology to address data science questions like visualization and representation of complex data sets, as well as the challenges posed by nontrivial topology when designing learning systems for prediction and classification. This work will be integrated into the educational program of the PI through the creation of an online TDA (Topological Data Analysis) academy, with the dual purpose of lowering the barrier of entry into the field for data scientists and academics, as well as increasing the representation of underserved communities in the field of computational mathematics. The project provides research training opportunities for graduate students.<br/><br/>Understanding the set of maps between topological spaces has led to rich and sophisticated mathematics, for it subsumes algebraic invariants like homotopy groups and generalized (co)homology theories. And while several data science questions are discrete versions of mapping space problems --- including nonlinear dimensionality reduction and supervised learning --- the corresponding theoretical and algorithm treatment is currently lacking. This CAREER award will contribute towards remedying this situation. The research program articulated here seeks to launch a novel research program addressing the theory and algorithms of how the underlying topology of a data set can be leveraged for data modeling (e.g., in dimensionality reduction) as well as when learning maps between complex data spaces (e.g., in supervised learning). This work will yield methodologies for the computation of topology-aware and robust multiscale coordinatizations for data via classifying spaces, a computational theory of topological obstructions to the robust extension of maps between data sets, as well as the introduction of modern deep learning paradigms in order to learn maps between non-Euclidean data sets.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

04/02/2024

07/21/2024

None

Grant

47.049

1

4900

4900

2415445

{'FirstName': 'Jose', 'LastName': 'Perea', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Jose Perea', 'EmailAddress': 'j.pereabenitez@northeastern.edu', 'NSF_ID': '000702108', 'StartDate': '04/02/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Northeastern University', 'CityName': 'BOSTON', 'ZipCode': '021155005', 'PhoneNumber': '6173733004', 'StreetAddress': '360 HUNTINGTON AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Massachusetts', 'StateCode': 'MA', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_ORG': 'MA07', 'ORG_UEI_NUM': 'HLTMVS2JZBS6', 'ORG_LGL_BUS_NAME': 'NORTHEASTERN UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Northeastern University', 'CityName': 'BOSTON', 'StateCode': 'MA', 'ZipCode': '021155005', 'StreetAddress': '360 HUNTINGTON AVE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Massachusetts', 'CountryFlag': '1', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_PERF': 'MA07'}

[{'Code': '126700', 'Text': 'TOPOLOGY'}, {'Code': '806900', 'Text': 'CDS&E-MSS'}]

['2020~27548', '2021~142901', '2022~147425', '2023~18675', '2024~14299']

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2415445.xml'}

SBIR Phase I: Respiratory dialysis for extracorporeal carbon dioxide treatment of COPD

NSF

08/15/2024

01/31/2025

{'Value': 'Standard Grant'}

{'Code': '15030000', 'Directorate': {'Abbreviation': 'TIP', 'LongName': 'Dir for Tech, Innovation, & Partnerships'}, 'Division': {'Abbreviation': 'TI', 'LongName': 'Translational Impacts'}}

{'SignBlockName': 'Edward Chinchoy', 'PO_EMAI': 'echincho@nsf.gov', 'PO_PHON': '7032927103'}

The broader impact of this Small Business Innovation Research (SBIR) Phase I project is the development of a novel extracorporeal approach removing excess CO2 from the blood of chronic obstructive pulmonary disease (COPD) patients. COPD is a leading cause of death globally and is responsible for over 550,000 hospitalizations in the US annually at a total yearly cost of $50 Billion. COPD leads to impaired quality of life, increased hospitalizations, and costs with poor overall prognosis despite modern interventions. Current end-stage treatments rely on mechanical ventilation, often resulting in further lung damage and high mortality rates. This project aims to develop an ultra-low-flow carbon dioxide removal system to support extubation, or avoid intubation, for providing respiration augmentation. The implementation of the therapy has the potential to reduce mechanical lung based interventions thereby improving patient outcomes, reducing adverse events associated with lung damage and diaphragmatic atrophy, and reducing overall hospitalization costs up to $17,000 per patient. <br/><br/> <br/>This Small Business Innovation Research (SBIR) Phase I project aims to optimize a prototype system providing respiratory dialysis to treat patients suffering from hypercapnic respiratory failure for extended durations. If successful, the project will address existing limitations of extracorporeal carbon dioxide removal techniques that requires high blood flow rates and specialized equipment. Results to date indicate significant increases in carbon dioxide capture efficiency versus existing methods, however risks and challenges remain in managing the removal of non-target ions and reducing dialysate waste generation. The specific objectives of this project are to develop a dialysate capable of capturing bicarbonate from the blood as a means of addressing hypercapnia while minimizing non-target and essential ions (K+, Mg2+, Ca2+). Additionally, this project aims to reduce the total dialysate usage requirement through a novel recirculation loop for dialysate recycling and reuse. If successful, the initiative will optimize dialysate composition and enable prolonged therapy while minimizing waste generation.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/07/2024

08/07/2024

None

Grant

47.084

1

4900

4900

2415446

{'FirstName': 'Nicholas', 'LastName': 'Williams', 'PI_MID_INIT': 'X', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Nicholas X Williams', 'EmailAddress': 'nick.williams@xcormed.com', 'NSF_ID': '000874494', 'StartDate': '08/07/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'X-COR THERAPEUTICS INC', 'CityName': 'WASHINGTON', 'ZipCode': '200122358', 'PhoneNumber': '2023861586', 'StreetAddress': '7144 13TH PL NW STE 2260', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'District of Columbia', 'StateCode': 'DC', 'CONGRESSDISTRICT': '00', 'CONGRESS_DISTRICT_ORG': 'DC00', 'ORG_UEI_NUM': 'C8ALEDEUU658', 'ORG_LGL_BUS_NAME': 'X-COR THERAPEUTICS INC.', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'X-COR THERAPEUTICS INC', 'CityName': 'Washington', 'StateCode': 'DC', 'ZipCode': '200122358', 'StreetAddress': '7144 13th Pl NW', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'District of Columbia', 'CountryFlag': '1', 'CONGRESSDISTRICT': '00', 'CONGRESS_DISTRICT_PERF': 'DC00'}

{'Code': '537100', 'Text': 'SBIR Phase I'}

2024~274274

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2415446.xml'}

Practitioner-Driven Synthesis of Museum Family Learning Conversations Research

NSF

09/01/2024

08/31/2027

{'Value': 'Standard Grant'}

{'Code': '11090000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DRL', 'LongName': 'Division Of Research On Learning'}}

{'SignBlockName': 'Jolene Jesse', 'PO_EMAI': 'jjesse@nsf.gov', 'PO_PHON': '7032927303'}

The Science Museum of Minnesota (SMM), in partnership with the University of Minnesota (UMN) and Bakken Museum, is conducting a Practitioner-Driven Synthesis of Museum Family Learning Conversations (FLC) Research. The project team, which includes researchers, librarians, museum educators, and experience designers, aims to bridge research and practitioner knowledges to produce bidirectional insights for the future of museum design and museum-based learning research. The research involves gathering, scoping, and synthesizing 25 years of research and evaluation on Family Learning Conversations conducted in museum settings, and formally incorporating practitioner-generated knowledge to spark the next generation of design and research on family learning in museums. This project is structured differently than a traditional synthesis in order to achieve the broadest impacts. Museum practitioners drive the synthesis, contributing their own practice-based knowledge, questions, and critical commentary to each part of the synthesis work. For practitioners, literature syntheses that identify how their existing ideas relate to research findings provide ecologically grounded and accessible insights for design. For researchers, understanding how practitioners identify learning or valuable interactions distinct from what has been valued in FLC research historically provides fertile ground for innovation in research methods and research questions. By bringing researchers with expertise in informal learning, video-based discourse analysis, and evidence synthesis into collaboration with museum educators, designers, and evaluators from institutions of varying size and emphases, the project is synthesizing research knowledge and practice knowledge that is fundamentally practitioner-driven, making knowledge in informal learning research more accessible to practitioners, and generating new questions and insights for further practical and research development.<br/><br/>This work contributes directly to advancing knowledge through synthesis of 25 years of museum Family Learning Conversations research in direct response to museum practitioners, while attending to how shifting values in museum education have shaped prior research and require new directions for future work. Using both rigorous literature synthesis processes and ongoing collaborative partnership with a cohort of museum educators, designers, and evaluators, the project is reactivating this literature and research approach, providing practical guidance for research design based in intertwined research and practitioner knowledges and charting a new vision forward for museum family learning research. The work involves first describing the existing knowledge of research and practitioners regarding design for FLC and then generating a focused mixed methods meta-synthesis on a practitioner-prioritized line-of-research. The project team is also engaging in a critical reflection on research methods used in FLC research and identifying underlying values shaping current knowledge and new avenues of investigation to further knowledge generation. Through targeted dissemination to museum practitioner and museum family learning researchers, the project aims to create bi-directional learning and to make the wealth of FLC research more accessible and interpretable through a rigorous synthesis that centers the values and priorities of museum practitioners at every stage of the work.<br/><br/>This Integrating Research and Practice project is funded by the Advancing Informal STEM Learning (AISL) program, which seeks to advance new approaches to, and evidence-based understanding of, the design and development of STEM learning in informal environments. This includes providing multiple pathways for broadening access to and engagement in STEM learning experiences.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/08/2024

08/25/2024

None

Grant

47.076

1

4900

4900

2415448

[{'FirstName': 'Amy', 'LastName': 'Grack Nelson', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Amy Grack Nelson', 'EmailAddress': 'agnelson@smm.org', 'NSF_ID': '000535150', 'StartDate': '08/25/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Marjorie', 'LastName': 'Bequette', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Marjorie Bequette', 'EmailAddress': 'mbequette@smm.org', 'NSF_ID': '000585129', 'StartDate': '08/08/2024', 'EndDate': '08/25/2024', 'RoleCode': 'Former Principal Investigator'}, {'FirstName': 'Megan', 'LastName': 'Goeke', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Megan Goeke', 'EmailAddress': 'mgoeke@smm.org', 'NSF_ID': '000791966', 'StartDate': '08/08/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'David', 'LastName': 'DeLiema', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'David DeLiema', 'EmailAddress': 'ddeliema@umn.edu', 'NSF_ID': '000825807', 'StartDate': '08/08/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]

{'Name': 'Science Museum of Minnesota', 'CityName': 'SAINT PAUL', 'ZipCode': '551021202', 'PhoneNumber': '7013174245', 'StreetAddress': '120 KELLOGG BLVD W', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Minnesota', 'StateCode': 'MN', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_ORG': 'MN04', 'ORG_UEI_NUM': 'FMBEN7W54M58', 'ORG_LGL_BUS_NAME': 'SCIENCE MUSEUM OF MINNESOTA', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Science Museum of Minnesota', 'CityName': 'SAINT PAUL', 'StateCode': 'MN', 'ZipCode': '551021202', 'StreetAddress': '120 KELLOGG BLVD W', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Minnesota', 'CountryFlag': '1', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_PERF': 'MN04'}

{'Code': '725900', 'Text': 'AISL'}

2024~499743

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2415448.xml'}

SBIR Phase I: The DTP-90 Thermoelectric Device with Distributed Transport Properties (DTP) for Refrigeration and Beyond

NSF

09/01/2024

08/31/2025

{'Value': 'Standard Grant'}

{'Code': '15030000', 'Directorate': {'Abbreviation': 'TIP', 'LongName': 'Dir for Tech, Innovation, & Partnerships'}, 'Division': {'Abbreviation': 'TI', 'LongName': 'Translational Impacts'}}

{'SignBlockName': 'Mara E. Schindelholz', 'PO_EMAI': 'marschin@nsf.gov', 'PO_PHON': '7032924506'}

The broader/commercial impact of this SBIR Phase I project is to enable a carbon reducing, energy efficient cooling and refrigeration solution, with far-reaching societal benefits. The novel thermoelectric cooling (TEC) module's portability and compactness are invaluable for applications requiring reliable and precise temperature control, such as medical devices, vaccine storage, and portable refrigerators used in transportation. In off-grid or remote environments where conventional refrigeration is impractical, these modules offer a lifeline for preserving medicines and perishable goods. This technology could prove crucial in disaster relief efforts, field hospitals, and everyday scenarios like camping trips, improving quality of life and access to essential services, particularly in regions with limited electricity. The thermoelectric cooling module has the potential to benefit society in numerous ways, from enhancing electronics efficiency and sustainability to providing critical cooling solutions for portable applications. The solid state thermoelectric device technology does not have any working fluids, offering an innovative solution to current refrigeration systems which contribute to increasing greenhouse gas (GHG) production. <br/><br/>The intellectual merit of this project is to produce distributed transport properties TEC modules using composite elements composed of materials with targeted transport properties informed by modeling and synthesized using conventional thermoelectric alloys. Distributed transport properties (DTP) is the optimal structuring of transport material properties, Seebeck coefficient, electrical resistivity, and thermal conductivity, within thermoelectric (TE) elements to create solid-state temperature control systems with greatly increased performance. The introduction of a Seebeck coefficient gradient within the TE elements partially counteracts detrimental distortion of the internal temperature profile induced by Joule heating. This technology will help portable refrigeration applications to be more efficient and less costly with increased portability. The Phase I objective is to produce a prototype DTP module which can achieve a maximum temperature difference greater than 90 Kelvin (K) with a 3 times increase in cooling efficiency (coefficent of performance (CoP)) and heat pumping at DT=70K as well as a pathway to large-volume manufacturing of DTP modules in the United States (US). The program goal is to combine DTP structure and additive manufacture to enable highly cost-effective manufacture in the US of the world’s best performing TE devices. These advancements can revolutionize both consumer and industrial applications for thermoelectric systems, contributing to a more sustainable and technologically advanced future.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/26/2024

08/26/2024

None

Grant

47.084

1

4900

4900

2415451

{'FirstName': 'Doug', 'LastName': 'Crane', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Doug Crane', 'EmailAddress': 'dcrane@dtpthermoelectrics.com', 'NSF_ID': '000849572', 'StartDate': '08/26/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'DTP THERMOELECTRICS LLC', 'CityName': 'PASADENA', 'ZipCode': '911072068', 'PhoneNumber': '6264973520', 'StreetAddress': '650 SIERRA MADRE VILLA AVE STE 2', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'California', 'StateCode': 'CA', 'CONGRESSDISTRICT': '28', 'CONGRESS_DISTRICT_ORG': 'CA28', 'ORG_UEI_NUM': 'NX9GVNE3UKP1', 'ORG_LGL_BUS_NAME': 'DTP THERMOELECTRICS LLC', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'DTP THERMOELECTRICS LLC', 'CityName': 'PASADENA', 'StateCode': 'CA', 'ZipCode': '911072068', 'StreetAddress': '650 SIERRA MADRE VILLA AVE STE 201', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'California', 'CountryFlag': '1', 'CONGRESSDISTRICT': '28', 'CONGRESS_DISTRICT_PERF': 'CA28'}

{'Code': '537100', 'Text': 'SBIR Phase I'}

2024~274773

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2415451.xml'}

Collaborative Research: CCF Core: Small: User-transparent Data Management for Persistence and Crash-consistency in Non-volatile Memories

NSF

11/15/2023

09/30/2026

{'Value': 'Standard Grant'}

{'Code': '05010000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CCF', 'LongName': 'Division of Computing and Communication Foundations'}}

{'SignBlockName': 'Danella Zhao', 'PO_EMAI': 'dzhao@nsf.gov', 'PO_PHON': '7032924434'}

Non-volatile memory is a type of computer memory that can retain stored data upon a power loss or system crash. Due to its large capacity and low energy footprint compared to traditional volatile memory, non-volatile memory has long been envisioned as an ideal solution for building large-scale, cost-effective, energy-efficient, and recoverable applications in many critical domains, including high-performance computing, machine learning, and embedded systems. Although non-volatile memory is available as commercial memory chips and offers numerous promises, it has not yet been widely adopted in production systems. The major obstacle is the difficulty to ensure that data is timely and correctly written to non-volatile memory, allowing it to be restored to a consistent state after a crash. Currently, application developers carry the burden of porting legacy applications to non-volatile memory, which is tedious and error-prone. This project seeks to establish a generic framework for user-transparent persistence and crash consistency that allows unmodified legacy applications to run efficiently and correctly with non-volatile memory. The success of this project will help unleash the full potential of non-volatile memory and make it easier to adopt. The research will also provide valuable insights into data management in future hybrid, disaggregated memory systems. In addition, this project involves mentoring Ph.D. students, engaging minority students, course development, and K12 outreach activities. <br/><br/>This project integrates non-volatile memory into the page/buffer cache in memory management – i.e., an abstraction that bridges the view of byte-addressable memory and a backing memory device -- to provide persistence and crash consistency to user-space programs with no or little user involvement. The challenges lie in 1) how to intercept program updates and redirect them to non-volatile memory for persistence; 2) how to properly order the updates and ensure update atomicity to guarantee crash consistency; 3) how to efficiently integrate non-volatile memory into page/buffer cache management without incurring noticeable overhead or performance degradation. This project addresses these challenges by focusing on persisting three types of program data – file-backed data, dynamically allocated application memory, and program metadata for virtual memory management, such as page tables, and exploring various software and hardware techniques, such as copy-on-write, undo logging, shadow paging, and extended page tables, for each data type to achieve efficient crash consistency. This project advances the understanding of hybrid memory management for volatile and non-volatile memories while simultaneously achieving high usability, good backward compatibility, and high efficiency.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

02/21/2024

02/21/2024

None

Grant

47.070

1

4900

4900

2415473

{'FirstName': 'Hui', 'LastName': 'Lu', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Hui Lu', 'EmailAddress': 'hui.lu@uta.edu', 'NSF_ID': '000751864', 'StartDate': '02/21/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'University of Texas at Arlington', 'CityName': 'ARLINGTON', 'ZipCode': '760199800', 'PhoneNumber': '8172722105', 'StreetAddress': '701 S NEDDERMAN DR', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Texas', 'StateCode': 'TX', 'CONGRESSDISTRICT': '25', 'CONGRESS_DISTRICT_ORG': 'TX25', 'ORG_UEI_NUM': 'LMLUKUPJJ9N3', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF TEXAS AT ARLINGTON', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'University of Texas at Arlington', 'CityName': 'ARLINGTON', 'StateCode': 'TX', 'ZipCode': '760199800', 'StreetAddress': '701 S. NEDDERMAN DR', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Texas', 'CountryFlag': '1', 'CONGRESSDISTRICT': '25', 'CONGRESS_DISTRICT_PERF': 'TX25'}

{'Code': '779800', 'Text': 'Software & Hardware Foundation'}

2023~200000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2415473.xml'}

Conference: International Workshop on Implication of Urban Scale Occupant Behavior for Resilient Building Design, Operation and Policy Making

NSF

02/01/2024

07/31/2024

{'Value': 'Standard Grant'}

{'Code': '07020000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'CBET', 'LongName': 'Div Of Chem, Bioeng, Env, & Transp Sys'}}

{'SignBlockName': 'Bruce Hamilton', 'PO_EMAI': 'bhamilto@nsf.gov', 'PO_PHON': '7032920000'}

Traditional occupant behavior modeling has been studied at the building level, and it has become an important factor in the investigation of building energy consumption. However, studies modeling occupant behaviors at the urban scale are still limited while such behavior is becoming a key factor in urban building and system energy modeling and energy policy making. Recent work has revealed that urban big data can enable occupant behavior modeling at the urban scale – however, utilizing existing data sources and modeling methods in building science to model urban scale occupant behaviors has challenges. The challenges for studying occupancy behavior at an urban scale are: (a) urban scale occupant behavior is stochastic and complex in nature; (b) lack of occupant behavior data sets to understand spatial and temporal diversity among all different buildings with different functions and occupant behaviors; and (c) lack of an appropriate modeling approach to integrate social demographical and equity with urban scale occupant movement inside and outside buildings. In addition, climate changes such as more extreme heat or cold events and power outages also affect occupants physiologically and psychologically and thus change their behavior. Modeling human behavior has been studied in other domains such as traffic analysis, epidemiology, communication, disaster management, and marketing. The goal of this workshop is to bridge the data sources and methodology gap between building science and beyond through bringing people from the multiple disciplines of building science, social science, energy policy, communication, civil engineering, transportation, public health, and others. The anticipated impact is significant contribution to foundational knowledge for improving the quality of urban living and reducing energy consumption. <br/><br/>The goal of urban scale occupant behavior research is to transform urban scale energy modeling and simulation, resilient building design and operation under future climates, and energy policy. The objective of this workshop is to identify the research gaps in existing urban scale occupant behavior research including what the obstacles are and identification of future research directions. The list of topics to discussed at the workshop includes: (1) What are the modeling requirements of occupant behavior at a community level? (2) What data sources have been used in other domains that could potentially enhance modeling capabilities for current building science applications? (3) What are new modeling methods of occupant behavior at a community level? and (4) What are potential future research directions for building design, operation, and policies at a community level, with enhanced data sources and modeling methods from other domains? This workshop will: (a) advance general knowledge of building science, engineering, and modeling through round-table discussions; (b) advance knowledge of methodological development in urban scale occupant behavior research for built environment through panel presentations and intensive technical discussions; (c) provide a collaborative platform for engineers, social science, policy and public health faculty and graduate students to exchange ideas; (d) provide future research directions and encourage enhanced involvement of faculty and students to participate in relevant research; (e) provide insights on better community building design and operation under future climates.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

03/13/2024

03/13/2024

None

Grant

47.041

1

4900

4900

2415488

{'FirstName': 'Bing', 'LastName': 'Dong', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Bing Dong', 'EmailAddress': 'bidong@syr.edu', 'NSF_ID': '000639898', 'StartDate': '03/13/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Syracuse University', 'CityName': 'SYRACUSE', 'ZipCode': '13244', 'PhoneNumber': '3154432807', 'StreetAddress': '900 S CROUSE AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'New York', 'StateCode': 'NY', 'CONGRESSDISTRICT': '22', 'CONGRESS_DISTRICT_ORG': 'NY22', 'ORG_UEI_NUM': 'C4BXLBC11LC6', 'ORG_LGL_BUS_NAME': 'SYRACUSE UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Syracuse University', 'CityName': 'SYRACUSE', 'StateCode': 'NY', 'ZipCode': '132440001', 'StreetAddress': '900 S CROUSE AVE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'New York', 'CountryFlag': '1', 'CONGRESSDISTRICT': '22', 'CONGRESS_DISTRICT_PERF': 'NY22'}

{'Code': '764300', 'Text': 'EnvS-Environmtl Sustainability'}

2024~48125

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2415488.xml'}

Developing resources to support community-responsive family program evaluation in informal STEM learning institutions

NSF

09/01/2024

08/31/2026

{'Value': 'Standard Grant'}

{'Code': '11090000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DRL', 'LongName': 'Division Of Research On Learning'}}

{'SignBlockName': 'Jolene Jesse', 'PO_EMAI': 'jjesse@nsf.gov', 'PO_PHON': '7032927303'}

The New York Hall of Science (NYSCI) will undertake a two-year Integrating Research and Practice project that will build the capacity of informal STEM educators to conduct evaluations of family STEM learning programs that are aligned with and responsive to the priorities and interests of program participants. The goal of this project is to test and develop resources that can support informal STEM educators and program developers in integrating meaningful, culturally responsive evaluation strategies into family STEM learning programs, particularly those that educators are responsible for evaluating themselves (a common scenario for ongoing programming in informal institutions). Through a collaborative research process, the research team will develop and test evaluation strategies that empower STEM educators to conduct reflexive and iterative evaluations that leverage and integrate caregiver perspectives and feedback. A resulting toolkit, developed within the context of NYSCI’s existing Families Learning Together program, will empower informal STEM educators to gather, interpret, and apply evidence and will contribute to the expertise of the informal STEM education workforce, the quality of the experiences they provide to learners, and the richness of the evaluation data available to project funders. The proposed project will extend and strengthen long-term partnerships between NYSCI, local community members, program evaluators, and other informal learning environments that work with largely Latine, new immigrant Spanish-speaking populations.<br/><br/>The project will move through four, overlapping phases of work. Phase 1 of the project will be an exploration of educator and participant alignment of metrics for success. Using a participatory research approach, researchers will collaborate with a group of caregivers that have participated in the NYSCI family program, Families Learning Together, identify the goals and values of family engagement programming, possible sources of evidence of its impact, and include caregivers in both the design and evaluation processes at NYSCI. Phase 2 will include systematic and collaborative data analysis and sense-making. Together with STEM practitioners and caregivers, researchers will work to identify potential tensions and opportunities to align practitioner expectations with caregiver values, agency, and engagement. In Phase 3, the research and practitioner team will develop resources that build the capacity of informal STEM educators to conduct evaluations of the programs they are responsible for evaluating themselves, through collaborative work with caregivers. Throughout the course of the project, the research and practitioner team will work with a group of four expert advisors to ensure that the strategies and resources created are relevant and feasible for educators at a range of institutions. Phase 4 will focus on communication and dissemination of project findings and resources to multiple stakeholders. This project will directly benefit caregivers from 45 Queens families who participate in the Families Learning Together program at NYSCI. The resources developed will help to improve evaluation practices and capacity in other informal STEM program settings, including science centers and children’s museums, and other community-based organizations that conduct evaluations to improve their programs.<br/><br/>This Integrating Research and Practice project is funded by the Advancing Informal STEM Learning (AISL) program, which seeks to advance new approaches to, and evidence-based understanding of, the design and development of STEM learning in informal environments. This includes providing multiple pathways for broadening access to and engagement in STEM learning experiences.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

07/11/2024

07/11/2024

None

Grant

47.076

1

4900

4900

2415503

[{'FirstName': 'Delia', 'LastName': 'Meza', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Delia Meza', 'EmailAddress': 'dmeza@nysci.org', 'NSF_ID': '000872922', 'StartDate': '07/11/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Diana', 'LastName': 'Ballesteros', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Diana Ballesteros', 'EmailAddress': 'dballesteros@nysci.org', 'NSF_ID': '000990452', 'StartDate': '07/11/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}]

{'Name': 'New York Hall of Science', 'CityName': 'CORONA', 'ZipCode': '113682950', 'PhoneNumber': '7185959173', 'StreetAddress': '4701 111TH ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'New York', 'StateCode': 'NY', 'CONGRESSDISTRICT': '06', 'CONGRESS_DISTRICT_ORG': 'NY06', 'ORG_UEI_NUM': 'UQ7FBRE34HS5', 'ORG_LGL_BUS_NAME': 'NEW YORK HALL OF SCIENCE', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'New York Hall of Science', 'CityName': 'CORONA', 'StateCode': 'NY', 'ZipCode': '113682950', 'StreetAddress': '4701 111TH ST', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'New York', 'CountryFlag': '1', 'CONGRESSDISTRICT': '06', 'CONGRESS_DISTRICT_PERF': 'NY06'}

{'Code': '725900', 'Text': 'AISL'}

2024~631404

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2415503.xml'}

Collaborative Research: Space for All: Creating Accessible Technology-Rich Makerspaces and Learning Activities for Youth and Young Adults with Autism

NSF

08/15/2024

07/31/2027

{'Value': 'Continuing Grant'}

{'Code': '11090000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DRL', 'LongName': 'Division Of Research On Learning'}}

{'SignBlockName': 'Wu He', 'PO_EMAI': 'wuhe@nsf.gov', 'PO_PHON': '7032920000'}

Hands-on technology-rich maker activities that combine computer programming, digital fabrication (e.g., 3D printing), and computer-aided design are shown to support learners’ empowerment, social competence, and technical training. However, existing maker activities and makerspaces are often not designed for learners with autism. This results in missed opportunities for including youth and young adults with autism in empowering and meaningful STEM learning experiences. This project will investigate how to design accessible and safe makerspaces and technology-rich maker activities for youth and young adults with disabilities, with input from therapists, special education teachers, psychologists, assistive technology experts, and learners themselves. The project will (1) create three accessible community makerspaces in Baltimore for learners with autism; (2) develop accessible technology-rich STEM learning activities for learners with autism and an educator training program to prepare out-of-school time educators to deliver them; (3) study the impact of participating in the activities on the learners’ empowerment and STEM attitudes and engagement, and the training on the educators’ self-efficacy and preparedness to deliver accessible STEM learning activities. The project will result in three accessible makerspaces in Baltimore and will directly impact 90 youth and young adults with autism and 20 educators and experts. The project will result in several resources that will support the development of accessible makerspaces and activities at other sites. These will include a design framework with guidelines, lessons learned, research findings, and an educator training module. This project is a collaboration between the Digital Harbor Foundation, University of Maryland Baltimore County, the Kennedy Krieger Institute, GWWO Architects, and MN Associates, Inc. <br/><br/>The project will use a mixed-methods approach to investigate how to create three accessible community makerspaces and technology-rich maker activities for youth and young adults with autism in Baltimore and how to prepare out-of-school time educators to deliver the learning activities, and will assess the impact of participating in the activities on learners’ empowerment and attitudes towards STEM and the educators’ preparedness to deliver STEM programs. The research will use qualitative data collection and analysis methods, including expert interviews and focus groups, youth focus groups, and co-design session observations. It will also use quantitative measures, including a modified Upper Elementary and Middle/High School Student Attitudes toward STEM survey, a retrospective technology self-efficacy survey, and pre-post surveys. Project research and resources will reach key audiences of learning scientists, special education experts, and out-of-school time educators through articles in peer-reviewed and practitioner journals, public events, and professional conferences. Project outcomes, including the design framework, will also be shared publicly through a project website and the Digital Harbor Foundation’s Localization Toolkit, which is an online resource for preparing equity-based learning programs across the nation, and the Kennedy Krieger’s School Programs network, which includes 16 school districts in Maryland.<br/><br/>This Integrating Research and Practice project is funded by the Advancing Informal STEM Learning (AISL) program, which supports projects that: (a) contribute to research and practice that considers informal STEM learning's role in equity and belonging in STEM; (b) promote personal and educational success in STEM; (c) advance public engagement in scientific discovery; (d) foster interest in STEM careers; (e) create and enhance the theoretical and empirical foundations for effective informal STEM learning; (f) improve community vibrancy; and/or (g) enhance science communication and the public's engagement in and understanding of STEM and STEM processes.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/07/2024

08/07/2024

None

Grant

47.076

1

4900

4900

2415505

[{'FirstName': 'Andrew', 'LastName': 'Coy', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Andrew Coy', 'EmailAddress': 'andrew@digitalharbor.org', 'NSF_ID': '000791853', 'StartDate': '08/07/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Justin', 'LastName': 'Watkins', 'PI_MID_INIT': 'B', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Justin B Watkins', 'EmailAddress': 'brent@digitalharbor.org', 'NSF_ID': '000992292', 'StartDate': '08/07/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]

{'Name': 'Digital Harbor Foundation', 'CityName': 'BALTIMORE', 'ZipCode': '212304017', 'PhoneNumber': '4436436085', 'StreetAddress': '1045 LIGHT STREET', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Maryland', 'StateCode': 'MD', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_ORG': 'MD07', 'ORG_UEI_NUM': 'FTMQYPJFCRB3', 'ORG_LGL_BUS_NAME': 'DIGITAL HARBOR FOUNDATION, INC.', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Digital Harbor Foundation', 'CityName': 'BALTIMORE', 'StateCode': 'MD', 'ZipCode': '212304017', 'StreetAddress': '1045 LIGHT STREET', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Maryland', 'CountryFlag': '1', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_PERF': 'MD07'}

{'Code': '725900', 'Text': 'AISL'}

2024~1091684

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2415505.xml'}

Collaborative Research: Space for All: Creating Accessible Technology-Rich Makerspaces and Learning Activities for Youth and Young Adults with Autism

NSF

08/15/2024

07/31/2027

{'Value': 'Continuing Grant'}

{'Code': '11090000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DRL', 'LongName': 'Division Of Research On Learning'}}

{'SignBlockName': 'Wu He', 'PO_EMAI': 'wuhe@nsf.gov', 'PO_PHON': '7032920000'}

Hands-on technology-rich maker activities that combine computer programming, digital fabrication (e.g., 3D printing), and computer-aided design are shown to support learners’ empowerment, social competence, and technical training. However, existing maker activities and makerspaces are often not designed for learners with autism. This results in missed opportunities for including youth and young adults with autism in empowering and meaningful STEM learning experiences. This project will investigate how to design accessible and safe makerspaces and technology-rich maker activities for youth and young adults with disabilities, with input from therapists, special education teachers, psychologists, assistive technology experts, and learners themselves. The project will (1) create three accessible community makerspaces in Baltimore for learners with autism; (2) develop accessible technology-rich STEM learning activities for learners with autism and an educator training program to prepare out-of-school time educators to deliver them; (3) study the impact of participating in the activities on the learners’ empowerment and STEM attitudes and engagement, and the training on the educators’ self-efficacy and preparedness to deliver accessible STEM learning activities. The project will result in three accessible makerspaces in Baltimore and will directly impact 90 youth and young adults with autism and 20 educators and experts. The project will result in several resources that will support the development of accessible makerspaces and activities at other sites. These will include a design framework with guidelines, lessons learned, research findings, and an educator training module. This project is a collaboration between the Digital Harbor Foundation, University of Maryland Baltimore County, the Kennedy Krieger Institute, GWWO Architects, and MN Associates, Inc. <br/><br/>The project will use a mixed-methods approach to investigate how to create three accessible community makerspaces and technology-rich maker activities for youth and young adults with autism in Baltimore and how to prepare out-of-school time educators to deliver the learning activities, and will assess the impact of participating in the activities on learners’ empowerment and attitudes towards STEM and the educators’ preparedness to deliver STEM programs. The research will use qualitative data collection and analysis methods, including expert interviews and focus groups, youth focus groups, and co-design session observations. It will also use quantitative measures, including a modified Upper Elementary and Middle/High School Student Attitudes toward STEM survey, a retrospective technology self-efficacy survey, and pre-post surveys. Project research and resources will reach key audiences of learning scientists, special education experts, and out-of-school time educators through articles in peer-reviewed and practitioner journals, public events, and professional conferences. Project outcomes, including the design framework, will also be shared publicly through a project website and the Digital Harbor Foundation’s Localization Toolkit, which is an online resource for preparing equity-based learning programs across the nation, and the Kennedy Krieger’s School Programs network, which includes 16 school districts in Maryland.<br/><br/>This Integrating Research and Practice project is funded by the Advancing Informal STEM Learning (AISL) program, which supports projects that: (a) contribute to research and practice that considers informal STEM learning's role in equity and belonging in STEM; (b) promote personal and educational success in STEM; (c) advance public engagement in scientific discovery; (d) foster interest in STEM careers; (e) create and enhance the theoretical and empirical foundations for effective informal STEM learning; (f) improve community vibrancy; and/or (g) enhance science communication and the public's engagement in and understanding of STEM and STEM processes.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/07/2024

08/07/2024

None

Grant

47.076

1

4900

4900

2415506

{'FirstName': 'Foad', 'LastName': 'Hamidi', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Foad Hamidi', 'EmailAddress': 'foadhamidi@umbc.edu', 'NSF_ID': '000763249', 'StartDate': '08/07/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'University of Maryland Baltimore County', 'CityName': 'BALTIMORE', 'ZipCode': '212500001', 'PhoneNumber': '4104553140', 'StreetAddress': '1000 HILLTOP CIR', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Maryland', 'StateCode': 'MD', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_ORG': 'MD07', 'ORG_UEI_NUM': 'RNKYWXURFRL5', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF MARYLAND BALTIMORE COUNTY', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'University of Maryland Baltimore County', 'CityName': 'BALTIMORE', 'StateCode': 'MD', 'ZipCode': '212500001', 'StreetAddress': '1000 HILLTOP CIR', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Maryland', 'CountryFlag': '1', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_PERF': 'MD07'}

{'Code': '725900', 'Text': 'AISL'}

2024~225705

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2415506.xml'}

RAPID: Multiplexed Distributed Acoustic Sensing (DAS) at the Ocean Observatory Initiative (OOI) Regional Cabled Array (RCA)

NSF

03/01/2024

02/28/2025

{'Value': 'Standard Grant'}

{'Code': '06040100', 'Directorate': {'Abbreviation': 'GEO', 'LongName': 'Directorate For Geosciences'}, 'Division': {'Abbreviation': 'OCE', 'LongName': 'Division Of Ocean Sciences'}}

{'SignBlockName': 'Kandace Binkley', 'PO_EMAI': 'kbinkley@nsf.gov', 'PO_PHON': '7032927577'}

Distributed Acoustic Sensing (DAS) is a relatively new observational technique in academia that interrogates an optical fiber with repeated laser pulses and utilizes changes in the phase of backscattered light to measure the strain rate along the fiber. If successful, this test will demonstrate the feasibility of multiplexed DAS on the Ocean Observatory Initiative’s (OOI) Regional Cabled Array (RCA)and would open the door for large-scale seafloor monitoring using the numerous existing telecom cables. Permanent, offshore DAS arrays have the potential to dramatically improve warning times for both great earthquakes in the Cascadia subduction zone. University of Washington postdocs will get experience leading data acquisition and quality control analysis.&lt;br/&gt;&lt;br/&gt;In November 2021 NSF-funded pilot experiment demonstrated the feasibility of making DAS observations using optical fibers in the two submarine cables of the Ocean Observatory Initiative’s (OOI) Regional Cabled Array (RCA) offshore Oregon. This test will take advantage of a planned brief maintenance shutdown to acquire both lit-fiber and dark-fiber DAS data on the same cable and with the same instrument to evaluate system performance. It will consist of a 4-day test of DAS on the OOI RCA in March 2024 using L-band DAS to record on lit fiber without interrupting ordinary RCA data telemetry. The advantage of a test that includes a shutdown is that we will observe both the DAS data quality with and without telecom data, as well as the telecom data quality with and without DAS.&lt;br/&gt;&lt;br/&gt;This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

02/02/2024

02/02/2024

None

Grant

47.050

1

4900

4900

2415521

[{'FirstName': 'Bradley', 'LastName': 'Lipovsky', 'PI_MID_INIT': 'P', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Bradley P Lipovsky', 'EmailAddress': 'bpl7@uw.edu', 'NSF_ID': '000785793', 'StartDate': '02/02/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Marine', 'LastName': 'Denolle', 'PI_MID_INIT': 'A', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Marine A Denolle', 'EmailAddress': 'marinedenolle@gmail.com', 'NSF_ID': '000709694', 'StartDate': '02/02/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'William', 'LastName': 'Wilcock', 'PI_MID_INIT': 'S', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'William S Wilcock', 'EmailAddress': 'wilcock@u.washington.edu', 'NSF_ID': '000096020', 'StartDate': '02/02/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]

{'Name': 'University of Washington', 'CityName': 'SEATTLE', 'ZipCode': '981951016', 'PhoneNumber': '2065434043', 'StreetAddress': '4333 BROOKLYN AVE NE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Washington', 'StateCode': 'WA', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_ORG': 'WA07', 'ORG_UEI_NUM': 'HD1WMN6945W6', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF WASHINGTON', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'University of Washington', 'CityName': 'SEATTLE', 'StateCode': 'WA', 'ZipCode': '981951016', 'StreetAddress': '4333 BROOKLYN AVE NE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Washington', 'CountryFlag': '1', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_PERF': 'WA07'}

{'Code': '1680', 'Text': 'OCEAN TECH & INTERDISC COORDIN'}

2024~198069

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2415521.xml'}

Equipment: WHOI/ARF SSSE Hydrostatic Wire Cutters

NSF

06/01/2024

05/31/2026

{'Value': 'Standard Grant'}

{'Code': '06040100', 'Directorate': {'Abbreviation': 'GEO', 'LongName': 'Directorate For Geosciences'}, 'Division': {'Abbreviation': 'OCE', 'LongName': 'Division Of Ocean Sciences'}}

{'SignBlockName': 'George Voulgaris', 'PO_EMAI': 'gvoulgar@nsf.gov', 'PO_PHON': '7032927399'}

Woods Hole Oceanographic Institution (WHOI) operates and manages the East Coast Winch Pool that was created by the U.S. National Science Foundation to support winch operations onboard vessels of the U.S. Academic Research Fleet (ARF) which are scheduled by the University-National Oceanographic Laboratory System (UNOLS). The facility acts as a center of expertise in winch use, maintenance, and engineering support. It provides portable winch systems in support of oceanographic research including expertise in tension member spooling for both portable and shipboard systems and the personnel to operate spooling equipment. This award would allow for the procurement of twenty-eight (28) hydrostatic wire cutters and twelve (12) weak links. The wire cutters and weak links would allow vessels in the ARF to free themselves from entrapment without exposing the crew to danger from breaking the tension member or the inordinate loss of tension member due to cutting it at the surface. The devices would increase safety during operations and minimize losses and thus increase cost-effectiveness. <br/><br/>The principal impact of the present proposal is under Merit Review Criterion 2 of the Proposal Guidelines (NSF 23-525). It provides infrastructure support for scientists to use the vessel and its shared-use instrumentation in support of their NSF-funded oceanographic research projects (which individually undergo separate review by the relevant research program of NSF). The acquisition, maintenance, and operation of shared-use instrumentation allows NSF-funded researchers from any US university or other organization access to well-maintained, high-quality, calibrated instruments for their research. It ensures the safe collection of high-quality oceanographic data in support of science, reduces the cost of that research, and expands the base of potential researchers.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

05/30/2024

05/30/2024

None

Grant

47.050

1

4900

4900

2415523

{'FirstName': 'Brian', 'LastName': 'Guest', 'PI_MID_INIT': 'J', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Brian J Guest', 'EmailAddress': 'bguest@whoi.edu', 'NSF_ID': '000859200', 'StartDate': '05/30/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Woods Hole Oceanographic Institution', 'CityName': 'WOODS HOLE', 'ZipCode': '025431535', 'PhoneNumber': '5082893542', 'StreetAddress': '266 WOODS HOLE RD', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Massachusetts', 'StateCode': 'MA', 'CONGRESSDISTRICT': '09', 'CONGRESS_DISTRICT_ORG': 'MA09', 'ORG_UEI_NUM': 'GFKFBWG2TV98', 'ORG_LGL_BUS_NAME': 'WOODS HOLE OCEANOGRAPHIC INSTITUTION', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Woods Hole Oceanographic Institution', 'CityName': 'WOODS HOLE', 'StateCode': 'MA', 'ZipCode': '025431535', 'StreetAddress': '266 WOODS HOLE RD', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Massachusetts', 'CountryFlag': '1', 'CONGRESSDISTRICT': '09', 'CONGRESS_DISTRICT_PERF': 'MA09'}

{'Code': '541600', 'Text': 'SHIPBOARD SCIENTIFIC SUPP EQUI'}

2024~93120

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2415523.xml'}

I-Corps: Translation Potential of Artificial Intelligence to Enhance Knowledge Graphs

NSF

05/15/2024

04/30/2025

{'Value': 'Standard Grant'}

{'Code': '15030000', 'Directorate': {'Abbreviation': 'TIP', 'LongName': 'Dir for Tech, Innovation, & Partnerships'}, 'Division': {'Abbreviation': 'TI', 'LongName': 'Translational Impacts'}}

{'SignBlockName': 'Molly Wasko', 'PO_EMAI': 'mwasko@nsf.gov', 'PO_PHON': '7032924749'}

The broader impact of this I-Corps project is based on the development of a cutting-edge solution for information management challenges that could have far-reaching implications across various commercial applications. By significantly reducing the time and effort required to organize and retrieve information from complex unstructured data, this solution provides a transformative approach to data management, especially for organizations dealing with large volumes of unstructured data. The benefit of this solution over current technologies is the ability to streamline decision-making processes, reduce work duplication, and enhance overall knowledge-worker productivity. This solution also has potential applications in academic settings, for example by assisting students in accessing information from multiple data sources and synthesizing conclusions. By adopting this new solution, large organizations and educational institutions can not only save time but could also unlock new insights from their vast amounts of stored, unstructured data.<br/><br/>This I-Corps project utilizes experiential learning coupled with a first-hand investigation of the industry ecosystem to assess the translation potential of the technology. The solution utilizes the power of artificial intelligence (AI) to transform unstructured data, such as complex documents, emails and PDFs, into organized, easily accessible information. The technology is a multi-layered knowledge graph, a data model that allows users to explore relationships and identify relevant datasets by combining characteristics of databases, graphs, and knowledge bases. This system links user-stored information and generates meta data for efficient organization and retrieval. The synthesis engine, powered by artificial generative intelligence and large language models, dynamically updates the knowledge graph, to synthesize summaries and connect related information. This innovative approach ensures that information systems stay current with the latest data inputs and user modifications, offering a cutting-edge solution for information management challenges.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

05/13/2024

05/13/2024

None

Grant

47.084

1

4900

4900

2415544

{'FirstName': 'Niloufar', 'LastName': 'Salehi', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Niloufar Salehi', 'EmailAddress': 'nsalehi@berkeley.edu', 'NSF_ID': '000807010', 'StartDate': '05/13/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'University of California-Berkeley', 'CityName': 'BERKELEY', 'ZipCode': '947101749', 'PhoneNumber': '5106433891', 'StreetAddress': '1608 4TH ST STE 201', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'California', 'StateCode': 'CA', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_ORG': 'CA12', 'ORG_UEI_NUM': 'GS3YEVSS12N6', 'ORG_LGL_BUS_NAME': 'REGENTS OF THE UNIVERSITY OF CALIFORNIA, THE', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'University of California-Berkeley', 'CityName': 'BERKELEY', 'StateCode': 'CA', 'ZipCode': '947101749', 'StreetAddress': '1608 4TH ST STE 201', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'California', 'CountryFlag': '1', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_PERF': 'CA12'}

{'Code': '802300', 'Text': 'I-Corps'}

2024~50000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2415544.xml'}

SBIR Phase I: Engineered Cell Lines with Activated Proteasomes for Increased Biomanufacturing Efficiency

NSF

07/01/2024

04/30/2025

{'Value': 'Standard Grant'}

{'Code': '15030000', 'Directorate': {'Abbreviation': 'TIP', 'LongName': 'Dir for Tech, Innovation, & Partnerships'}, 'Division': {'Abbreviation': 'TI', 'LongName': 'Translational Impacts'}}

{'SignBlockName': 'Erik Pierstorff', 'PO_EMAI': 'epiersto@nsf.gov', 'PO_PHON': '7032922165'}

The broader impact of this Small Business Innovation Research (SBIR) Phase I project will be to reduce the costs associated with the biomanufacturer of advanced therapies by making their manufacture more efficient. This project seeks to test the feasibility and application of a novel technology to significantly increase the protein production capabilities of cell lines currently used in the manufacture of biologics, gene therapies, and vaccines. Achievement of this project’s objectives could enhance the health and welfare of Americans by making advanced therapies more economically accessible. As the population ages, the prevalence of debilitating diseases like Alzheimer's and cancer is on the rise. This project could make the solutions to these issues more affordable and effective, significantly impacting the quality of life of Americans. In addition, this project could help revolutionize treatment for rare genetic disorders by overcoming the current hurdles of high manufacturing costs, thereby broadening access to these vital treatments. <br/><br/>The proposed project seeks to build on initial data showing that enhancement of the cellular proteasome has an unexpected and counterintuitive effect on protein production in cells. The aims will be to demonstrate that this technology can be applied to cells commonly used in the manufacture of advanced therapies and that it can enhance the production of protein types relevant to human health such as gene therapy vectors and biologic drugs. Successful completion of this project will also provide new insights into the function of cells used in biomanufacturing and potentially enable further innovation in this area to ease this bottleneck on the production of advanced therapies.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

06/17/2024

06/17/2024

None

Grant

47.084

1

4900