Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Optimizing Retail Operation With Real-Time Customer Activity Intelligence (SENSEI)

Framework: Horizon 2020 — Industrial Leadership
Programme: Information and Communication Technologies
Action type: SME instrument
Countries involved: Portugal
Call: Open Disruptive Innovation Scheme (H2020-SMEINST-1-2016-2017, 2017)
Start date: 2018-02-01
End date: 2018-07-31
Duration (months): 6.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

Brick and mortar stores still generate 89% of the total volume of sales in Europe. Not knowing lost sales statistics creates a major blind spot. Not knowing lost sales statistics might lead to over/understaffing stores, stocking the wrong inventory and missing opportunities due to price or product placement. There is a clear need for lost sales based business intelligence that gives store managers the agility to optimize resources and maximize sales. They need lost sales and sales information to detect trends early and be proactive. Our technology SENSEI enables retailers to gather lost sales data and merge it with their sales data by using every store as a customer research lab, allowing the development of effective customer-centric strategies. SENSEI is built on 1) computer vision, 2) sensors and 3) in-store devices, and is able to provide precise information about how each visitor is interacting with the store space even if they don’t buy. We have identified our target market as the fashion and apparel retail chains, where store footprints are small (when compared with grocery), highly scalable due to multiple heavily standardized stores, and with a strong need and appetite to invest in data analytics and business intelligence. Smart cities involve optimizing information technology to better understand our infrastructures and the behaviors of people and to be able to make informed decisions that meet the needs of citizens, institutions, and companies with a view to the community and sustainable development. SENSEI does exactly that for stores. In the long run, our technology will definitely contribute to Smart Cities on a larger scale. The founders’ vision when creating SENSEI was to fill a gap in the market and that is destined to create real smart stores. They believe with high certainty that both market share and revenue projections will be achieved within the projected time frame. We are already using SENSEI with a series of pilot users.

Keywords: proprietary computer vision algorithms,unmatched centimeter based level of accuracy,non sales based business intelligence omni channel approach,analytics engine
Enhancing the innovation management capacities of SMEs in East Poland (KAM2EastPoland2020-2021)

Framework: Horizon 2020 — Industrial Leadership
Programme: Innovation in SMEs
Action type: Specific Grant agreement
Countries involved: Poland,Poland,Poland,Poland
Call: H2020 ENTREPRISE EUROPE NETWORK SGA4 2020-2021 (H2020-EEN-SGA4-2020-2021, 2019)
Start date: 2020-01-01
End date: 2021-12-31
Duration (months): 24.0
Total project cost (EUR): 77420.0
EU funding (EUR): 77420.0
Participants: 6
Project status: CLOSED

The main objective of the project is to facilitate the access to European and international markets by providing growthoriented, integrated business and innovation support services that will help to strengthen the competitiveness and sustainability of the enterprises in the EU countries. The proposal also focuses on strengthening the collaboration between different key actors in the innovation chain. Main objective of the project will be implemented by specific objectives: 1. Economic potential increase among enterprises benefiting from SME Instrument in the framework of Horizon 2020 by ensuring that the SME Instrument beneficiaries will receive the most appropriate services to enhance the probability of successful exploitation of the innovation project supported by the Instrument and to leave a footprint for the future sustainable growth of the beneficiary by identifying bottlenecks and indicated solutions with the help of a capable coach. This objective will be implemented by the tailor made service of The Key Account Management (KAM) in the framework of WP1. 2. Increase of innovation potential of small and medium sized enterprises by providing hider quality innovation support services. This objective will be implemented by specially designed activity: Enhancing the innovation management capacity of SMEs (EIMC) in the framework of WP2 of this project and will be addressed to SMEs with a real potential for international growth via product, process, service or business model innovation but lack the knowledge, skills or ability to manage innovation activities. The main goal of the service is to make the innovation system, in the company, more efficient and effective. Specific objectives will be implemented by five Partners of Enterprise Europe Network East Poland Consortium. All Partners have relevant staff members with skills, knowledge and experience to provide specialised services. Project duration is foreseen for 24 months.

Keywords: innovation management,capacity building,innovation expert,horizon 2020,key account management,enhancing innovation management
How changing social contexts shape solidarity and adjustment between generations (SHAPINGENERATIONS)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Individual Fellowships (IF)-Standard European Fellowships
Action type: Marie Skłodowska-Curie actions
Panel: Social Sciences and Humanities
Countries involved: United Kingdom
Call: Individual Fellowships (H2020-MSCA-IF-2017, 2017)
Start date: 2019-09-01
End date: 2024-03-31
Duration (months): 24.0
Total project cost (EUR): 195454.8
EU funding (EUR): 195454.8
Participants: 1
Project status: TERMINATED

The sustainability of the welfare state in which the state plays a key role in the promotion of solidarity, integration and wellbeing of its citizens may be compromised due to the current economic crisis and unprecent demographic changes. The combination of these pressures with new family forms, pose significant challenges to individuals, families and societies and place solidarity and adjustment between generations as a priority in European states, arguably more important today than in earlier decades, as people live longer and share more years with younger generations. The aim of this proposal is to investigate how the social context, from macro-societal to micro-interpersonal, affects intergenerational solidarity and important indicators of adjustment between generations in two economically and culturally distinct countries: Portugal and UK. The project seeks to examine: national (e.g., policies), regional (e.g. economic circumstances), family (e.g. transfers up and down family lineages) and individual-level relationships (e.g., wellbeing). Mixed-methods will be used to facilitate an integrated approach from macrosocietal to individual variables and enable empirical-base and sound policy making. A synthesis of the findings will focus on the levels of context that can be powerful in shaping inequalities in intergenerational solidarity, well-being and social integration and on the implications for programmes and policies. The strong theory-driven nature of the project, the candidate profile, the international mobility and working in a world-renowned centre of excellence with the support from a dynamic multidisciplinary team representing a wide range of substantive, methodological and policy expertise, are key factors for the project’s impact and candidate career development, skills acquisition and diversification. The project and the candidate career will also benefit from the input and initiatives funded by ongoing topic-related projects (e.g., Cost ActionIS1311)

Keywords: solidarity between generations,social integration,health and well being,demographic and economic pressures,translational and interdisciplinary research
Maintaining the Human Mitochondrial Genome (DELMIT)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Consolidator grants
Action type: ERC actions
Panel: Molecules of Life: Biological Mechanisms, Structures and Functions
Panel description: Molecular biology, biochemistry, structural biology, molecular biophysics, synthetic and chemical biology, drug design, innovative methods and modelling
Countries involved: Sweden
Call: ERC Consolidator Grant (ERC-2015-CoG, 2015)
Start date: 2016-11-01
End date: 2022-04-30
Duration (months): 66.0
Total project cost (EUR): 1999985.0
EU funding (EUR): 1999985.0
Participants: 1
Project status: CLOSED

Mitochondria are required to convert food into usable energy forms and every cell contains thousands of them. Unlike most other cellular compartments, mitochondria have their own genomes (mtDNA) that encode for 13 of the about 90 proteins present in the respiratory chain. All proteins necessary for mtDNA replication, as well as transcription and translation of mtDNA-encoded genes, are encoded in the nucleus. Mutations in nuclear-encoded proteins required for mtDNA maintenance is an important cause of neurodegeneration and muscle diseases. The common result of these defects is either mtDNA depletion or accumulation of multiple deletions of mtDNA in postmitotic tissues. The long-term goal (or vision) of research in my laboratory is to understand in molecular detail how mtDNA is replicated and how this process is regulated in mammalian cells. To this end we use a protein biochemistry approach, which we combine with in vivo verification in cell lines. My group was in 2004 the first to reconstitute mtDNA replication in vitro and we have continued to develop even more elaborate system ever since. In the current application, the major focus is studies of the mitochondrial D-loop region, a triple-stranded structure in the mitochondrial genome. The D-loop functions as a regulatory hub and we will determine how initiation and termination of mtDNA replication is controlled from this region. We will also determine the physical organization of the mtDNA replication machinery at the replication fork and establish how mtDNA deletions, a classical hallmark of human ageing, are formed.

Keywords: dna polymerase,helicase,primase,ageing and mitochondria
innovative MachIne leaRning to constrain Aerosol-cloud CLimate Impacts (iMIRACLI) (iMIRACLI)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Innovative Training Networks (ITN)-European Training Networks
Action type: Marie Skłodowska-Curie actions
Panel: Environment and Geosciences
Countries involved: Germany,Spain,Germany,Switzerland,Switzerland,Sweden,United Kingdom,United Kingdom,United Kingdom
Call: Innovative Training Networks (H2020-MSCA-ITN-2019, 2019)
Start date: 2020-01-01
End date: 2024-06-30
Duration (months): 54.0
Total project cost (EUR): 4185717.12
EU funding (EUR): 4185717.12
Participants: 9
Project status: SIGNED

Climate change is one of the most urgent problems facing mankind. Implementation of the Paris climate agreement relies on robust scientific evidence. Yet, the uncertainty of non-greenhouse gas forcing associated with aerosol-cloud interactions limits our constraints on climate sensitivity. Radically new ideas are required. While the majority of forcing estimates are model based, model uncertainties remain too large to achieve the required uncertainty reductions. The quantification of aerosol cloud climate interactions in Earth Observations is thus one of the major challenges of climate science. Progress has been hampered by the difficulty to disentangle aerosol effects on clouds and climate from their covariability with confounding factors, limitations in remote sensing, very low signal-to-noise ratios as well as computationally, due to the scale of the big (>100Tb) datasets and their heterogeneity. Such big data challenges are not unique to climate science but occur across a wide range of data science applications. Innovative techniques developed by the AI and machine learning community show huge potential but have not yet found their way into climate sciences – and climate scientists are currently not trained to capitalise on these advances. The central hypothesis of IMIRACLI is that merging machine learning and climate science will provide a breakthrough in the exploration of existing datasets, and hence advance our understanding of aerosol-cloud forcing and climate sensitivity. Its innovative training plan will match each ESR with supervisors from climate and data sciences as well as a non-academic advisor and secondment and provide them with state-of-the-art data and climate science training. Partners from the non-academic sector will be closely involved in each of the projects and provide training in a commercial context. This ETN will produce a new generation of climate data scientists, ideally trained for employment in the academic and commercial sectors.

Keywords: cloud,aerosol,climate,data science,machine learning
Safe data-driven control for human-centric systems (CO-MAN)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Consolidator grants
Action type: ERC actions
Panel: Systems and communication engineering
Panel description: Electrical, electronic, communication, optical and systems engineering
Countries involved: Germany
Call: ERC Consolidator Grant (ERC-2019-COG, 2019)
Start date: 2020-09-01
End date: 2025-08-31
Duration (months): 60.0
Total project cost (EUR): 1999975.0
EU funding (EUR): 1999975.0
Participants: 1
Project status: SIGNED

Many control systems of the future involve a tight interaction or even symbiosis with the human user. High-impact application domains of human-centric systems include healthcare, mobility, and infrastructure systems. In human-centric systems the human is both, an element of the control system, and a design criterion with individual requirements that need to be satisfied. Safety - despite the high uncertainty of human behavior - and maximization of individual user experience are the primary objectives for control design in human-centric systems. The visionary goal of CO-MAN is to contribute to the fundamental understanding and principled approach to the control of smart human-centric systems. We will develop a novel framework for user-adaptive data-driven control with performance guarantees in order to address the scientific challenges of high uncertainty and individual user requirements. The grand challenge is to unify the two previously separate paradigms of model-based control with its rigorous guarantees but limited modeling base and machine learning algorithms with its flexible modeling concepts but lack of guarantees. The breakthrough enabling idea is to merge probabilistic non-parametric modeling techniques from statistical learning theory with novel risk-aware control methodologies while including active user modeling. The game changer is the current push towards reliable machine learning with novel results on theoretical bounds for learning behavior. Because of favorable properties we will focus on Gaussian Processes to model user behavior and preferences and translate the naturally quantified model uncertainty into closed loop behavior guarantees through a confidence-driven human-interactive control approach. The PI is in a perfect position to achieve the envisioned goal of super-individualized data-driven control with performance guarantees given the highly visible preliminary results and leadership in the area of human-cyber-physical systems.

Keywords: human centric control systems,human interactive data driven control
HEalth related Activity Recognition system based on IoT – an interdisciplinary training program for young researchers (HEART)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Innovative Training Networks (ITN)-European Industrial Doctorates
Action type: Marie Skłodowska-Curie actions
Panel: Information Science and Engineering
Countries involved: Germany,Italy,Italy,Belgium,China,Netherlands
Call: Innovative Training Networks (H2020-MSCA-ITN-2017, 2017)
Start date: 2017-09-01
End date: 2021-08-31
Duration (months): 48.0
Total project cost (EUR): 1527991.2
EU funding (EUR): 1527991.2
Participants: 9
Project status: CLOSED

A current trend in healthcare involves the prevention of chronic diseases by changing behaviour towards more healthy lifestyle choices. This is supported by the increased use of wearable sensors and Internet of Things (IoT) devices. Human activity recognition and vital sign monitoring play a significant role in tailoring personal health and behaviour change coaching solutions to each individual, but pose a number of technical, legal, and socio-economic issues, which must be solved to enable a commercial viable solution. The IoT is a key growth business area for EU firms, which need to acquire competencies and skills for the exploitation of their innovation potential abroad. China is a key destination market, but products and solutions have to be tailored to the needs, behaviours and habits of Chinese consumer and to the specificity of the market. The goals of HEART project are: • to allow the formation of a team of 6 researchers, with a strong interdisciplinary attitude, integrating social science and humanities with high-end technical skills, creativity, innovation and entrepreneurial allure, with teamwork capabilities and ability to operate in the Chinese context for business in the domain of IoT and healthcare; • to release a health integrated activity recognition platform able to detect activities from heterogeneous data, using scalable algorithms, while safeguarding the privacy of the persons. A priority for the Non Academic beneficiary’s competitiveness is to deliver wearable technology for health monitoring, primary dedicated to healthy people (of +40 age) to penetrate the Chinese market; • to address the growing need of EU firms, for employees having the necessary skills (technical, legal and economic) in the IoT domain, thus increasing their international competitiveness. The consortium is composed of Philips, KU Leuven and the UNIMC with strong interdisciplinary experience in all relevant fields of HEART, supported by a network of partners in EU and China.

Keywords: internet of things,human activity recognition,healthcare,well being,wearable sensors,context aware sensors,privacy by design,international business,china
Defect Analysis and Thermal Effects of Nanolasers and Emitters (DATENE)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Individual Fellowships (IF)-Society and Enterprise panel
Action type: Marie Skłodowska-Curie actions
Panel: Physics
Countries involved: Switzerland
Call: Individual Fellowships (H2020-MSCA-IF-2018, 2018)
Start date: 2020-01-01
End date: 2022-03-01
Duration (months): 24.0
Total project cost (EUR): 203149.44
EU funding (EUR): 203149.44
Participants: 1
Project status: CLOSED

Photonic integrated circuits (PIC) are becoming a key contender for the next generation of communication. Two main barriers exist for the seamless integration of electronics and photonics, the integration of active photonic components on the silicon chip, and their downsizing towards electronic dimensions. III-Vs with their tunable direct bandgaps are the materials of choice for integrated lasers on Si. IBM has achieved room-temperature III-V optically pumped microdisk lasers monolithically on Si. Defects in the III-V material when grown on Si is a main factor in reducing the efficiency of optical devices, and can also lead to catastrophic failure of devices. Hence the ability to analyze and preferably control their impact is essential for integrated photonics. Another equally grand challenge for advanced technologies today is thermal management of photonic devices on Si, at all levels of system integration from the package down to individual devices. Whereas this is true for electronics, thermal effects are even more severe for photonic devices. Although downscaling of photonic components is ultimately limited by diffraction, thermal effects (wavelength shift and self-heating), in practice play a great role. The present proposal addresses these two great challenges in integrated photonics: a) Defect analysis of III/V nanoscale photonic devices – morphological and device characterization to understand the impact of material defects on device, reliability studies. b) Nanoscale thermal management of active III-V lasers on Si – by a combination of in-situ nanoscale thermal characterization and thermal stress simulation. To address this, I will apply my extensive experience and skills in thermal characterization and defect analysis which complement the existing competences at IBM, on III-V materials, device fabrication and scanning thermal microscopy.

Keywords: semiconductor lasers,defect analysis,thermal transport,failure analysis
A Functional, Mature In vivo Human Ventricular Muscle Patch for Cardiomyopathy (5D Heart Patch)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Advanced grants
Action type: ERC actions
Panel: Prevention, Diagnosis and Treatment of Human Diseases
Panel description: Medical technologies and tools for prevention, diagnosis and treatment of human diseases, therapeutic approaches and interventions, pharmacology, preventative medicine, epidemiology and public health, digital medicine
Countries involved: Sweden
Call: ERC Advanced Grant (ERC-2016-ADG, 2016)
Start date: 2017-12-01
End date: 2022-11-30
Duration (months): 60.0
Total project cost (EUR): 2149227.5
EU funding (EUR): 2149227.5
Participants: 1
Project status: CLOSED

Developing new therapeutic strategies for heart regeneration is a major goal for cardiac biology and medicine. While cardiomyocytes can be generated from human pluripotent stem (hPSC) cells in vitro, it has proven difficult to use these cells to generate a large scale, mature human heart ventricular muscle graft on the injured heart in vivo. The central objective of this proposal is to optimize the generation of a large-scale pure, fully functional human ventricular muscle patch in vivo through the self-assembly of purified human ventricular progenitors and the localized expression of defined paracrine factors that drive their expansion, differentiation, vascularization, matrix formation, and maturation. Recently, we have found that purified hPSC-derived ventricular progenitors (HVPs) can self-assemble in vivo on the epicardial surface into a 3D vascularized, and functional ventricular patch with its own extracellular matrix via a cell autonomous pathway. A two-step protocol and FACS purification of HVP receptors can generate billions of pure HVPs- The current proposal will lead to the identification of defined paracrine pathways to enhance the survival, grafting/implantation, expansion, differentiation, matrix formation, vascularization and maturation of the graft in vivo. We will captalize on our unique HVP system and our novel modRNA technology to deliver therapeutic strategies by using the in vivo human ventricular muscle to model in vivo arrhythmogenic cardiomyopathy, and optimize the ability of the graft to compensate for the massive loss of functional muscle during ischemic cardiomyopathy and post-myocardial infarction. The studies will lead to new in vivo chimeric models of human cardiac disease and an experimental paradigm to optimize organ-on-organ cardiac tissue engineers of an in vivo, functional mature ventricular patch for cardiomyopathy