October 2020 COVID Research Lightning Talks: Webinar + Q&A
Channel: Northeast Big Data Innovation Hub
Date: 16/10/2020

Meet the scientists seeking new insights on COVID-19. Every month, we bring together a group of researchers studying wide-ranging aspects of the current pandemic, to share their research and answer questions from our community. Learn more about their ongoing efforts in the fight against COVID-19, including opportunities for collaboration.

This webinar features the following speakers: 

Rachel Wu, University of California-Riverside: RAPID: Older adults' learning and adaptation as resilience processes to counter social isolation during the COVID-19 pandemic. Funded by NSF Social, Behavioral and Economics Sciences / Behavioral and Cognitive Sciences.
📜 Read an English Transcription of this presentation: https://bit.ly/3IGpjBw

Sara Rampazzi, University of Michigan: RAPID: SaTC: COVID19: Science of using wirelessly powered sensors to quickly scale up verifiable decontamination of individual N95 respirator masks. Funded by NSF Computer and Information Science and Engineering / Computer and Network Systems.
📜 Read an English Transcription of this presentation: https://bit.ly/3ICpzl1

Sarah Bowman, Hauptman-Woodward Medical Research Institute, University at Buffalo: RAPID Enhanced SARS-CoV-2 High-Throughput Crystallization for Structural Studies. Funded by NSF Biological Sciences / Biological Infrastructure.
📜 Read an English Transcription of this presentation: https://bit.ly/3vuJqi3

Samantha Penta, University at Albany: RAPID: A Multi-Wave Study of Risk Perception, Information Seeking, and Protective Action in COVID-19. Funded by NSF Engineering / Civil, Mechanical and Manufacturing Innovation.
📜 Read an English Transcription of this presentation: https://bit.ly/3tHUxC3

Murat Kantarcioglu, University of Texas at Dallas: RAPID: Collaborative: A Privacy Risk Assessment Framework for Person-Level Data Sharing During Pandemics. Funded by NSF Computer and Information Science and Engineering / Computer and Network Systems.
📜 Read an English Transcription of this presentation: https://bit.ly/3HAKcN8

Ali Rahnavard, George Washington University: RAPID: A novel platform for data integration and deep learning on COVID-19. Funded by NSF Biological Sciences / Environmental Biology.
📜 Read an English Transcription of this presentation: https://bit.ly/3hxUItP

Jeff Grann, Credential Engine: RAPID: Increasing Healthcare Credential Open Data in Response to COVID-19. Funded by NSF Office of the Director / Office of Integrative Activities.
📜 Read an English Transcription of this presentation: https://bit.ly/3pvENR4

Praveen Rao, University of Missouri-Columbia: RAPID: Democratizing Genome Sequence Analysis for COVID-19 Using CloudLab. Funded by NSF Computer and Information Science and Engineering / Computer and Network Systems.
📜 Read an English Transcription of this presentation: https://bit.ly/3vyAsk4

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Timestamps:
06:58 Rachel Wu, UC Riverside
12:38 Sara Rampazzi, University of Michigan; University of Florida
17:59 Sarah EJ Bowman, Hauptman Woodward Medical Research Institute
23:31 Samantha Penta, University at Albany
29:08 Murat Kantarcioglu, University of Texas at Dallas
35:24 Ali Rahnavard, George Washington University
41:48 Jeff Grann, Credential Engine
48:29 Praveen Rao, University of Missouri-Columbia
55:31 Q&A Session

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💻 Learn more about the COVID Information Commons: https://covidinfocommons.datascience.columbia.edu/

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