Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
CONFERENCE ON RESEARCH AND INNOVATION IN LEVERAGING TECHNOLOGY TO STRENGTHEN THE EU COMPETITIVENESS IN LIFE SCIENCES (LIFESCIENCE4EU)

Framework: Horizon Europe — Global Challenges and European Industrial Competitiveness
Programme: Health
Theme: Health
Destination: Other health destinations
Action type: Coordination and support actions
Countries involved: Poland
Call: Presidency event - Poland. Research and Innovations for health and quality of life - how to exploit the exponential growth of possibilities (HORIZON-HLTH-2024-PPOL-16-IBA, 2024)
Start date: 2025-01-01
End date: 2025-06-30
Duration (months): 6.0
Total project cost (EUR): 343250.0
EU funding (EUR): 300000.0
Participants: 1
Project status: SIGNED

The project "Conference on research and innovation in leveraging technology to strengthen the EU competitiveness in life sciences (LIFESCIENCE4EU)" aims to organize a conference during the Polish Presidency of the Council of the European Union, scheduled for 15-16 May 2025 in Kraków. This event will spotlight the integration of advanced technologies to address healthcare challenges and improve global quality of life. Key objectives include aligning with EU health priorities to build a resilient and independent health sector, fostering collaboration across research, development, regulatory bodies, and patient advocacy groups, and promoting innovations such as digital health, AI, and biotechnology. The conference will explore strategies to overcome regulatory barriers, enhance local healthcare manufacturing, and scale emerging technologies. Additionally, it will create a platform for networking, knowledge exchange, and the dissemination of best practices to maximize the impact of healthcare innovations and foster a collaborative ecosystem across Europe.

Keywords: technology,digital health,life sciences,research,innovation
Prediction error computation in visual perception (PreVision)

Framework: Horizon Europe — Excellent Science
Programme: Marie Skłodowska-Curie Actions (MSCA)
Theme: Marie Skłodowska-Curie
Destination: Postdoctoral Fellowships
Action type: Marie Skłodowska-Curie actions
Panel: Social Sciences and Humanities
Countries involved: Spain
Call: MSCA Postdoctoral Fellowships 2023 (HORIZON-MSCA-2023-PF-01, 2023)
Start date: 2024-04-01
End date: 2026-03-31
Duration (months): 24.0
Total project cost (EUR): 181152.96
EU funding (EUR): 181152.96
Participants: 1
Project status: SIGNED

Prior knowledge plays a central role in shaping our perception and interactions with the world. Predictive coding theories represent an influential framework formalizing the neural computations that underlie the integration of prior knowledge into perception. One central tenet of predictive coding is the computation of prediction errors, which signify the discrepancy between predictions, derived from our prior knowledge, and incoming sensory input. Despite ample empirical evidence supporting the existence of prediction errors, such as heightened sensory responses to unexpected compared to expected stimuli, several unresolved questions persist. One pivotal question pertains to the nature of the surprise encoded in sensory prediction errors across the visual cortical hierarchy. Does the computation of prediction errors reflect local surprise, specific to each level in the visual hierarchy (e.g., surprising orientations in primary visual cortex)? Alternatively, is the coding of surprise inherited top-down, aligning with the notion of predictive coding that predictions are relayed from higher to lower areas? Furthermore, it remains unclear whether the computation of surprise dynamically adapts to our goals or remains a static feature of cortical tuning. Lastly, the networks and temporal dynamics that underlie prediction and prediction error computations are poorly understood. Within the scope of the PreVision project, my objective is to address these critical knowledge gaps through the integration of advanced neuroimaging techniques and artificial intelligence methodologies, thereby shedding light on the fundamental neurocomputational mechanisms that drive perception. Consequently, this project represents an excellent opportunity for me to engage in innovative and pioneering research, investigating pressing questions within contemporary cognitive neuroscience, and significantly advance my scientific career.

Keywords: cognitive neuroscience,predictive coding,vision,perception,artificial neural networks,task goals,eeg,fmri
Hydrogel Machines for Seamless Living System Interfaces (GELECTRO)

Framework: Horizon Europe — 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 GRANTS (ERC-2023-COG, 2023)
Start date: 2024-07-01
End date: 2029-06-30
Duration (months): 60.0
Total project cost (EUR): 1999473.0
EU funding (EUR): 1999473.0
Participants: 1
Project status: SIGNED

Bioelectronic interfaces are machines designed to exchange information with living matter. They are opening new frontiers in medicine. For example, machines implanted in the body may soon enable repair of damaged tissues or replacement of functions affected by chronic disease. The realisation of this vision is impeded by the available hardware. Today’s materials, devices and systems are electronic, while soft living matter uses ions and molecules for communication and computation. The central hypothesis of GELECTRO is: electrically conductive hydrogels can enable bioelectronic machines that are multimodal and nearly indistinguishable from the biological host. The project will thus contribute a new class of interfacing technologies that are made almost entirely of water. If successful, they will not only blur the boundary with the host, but also tap into the control loops that organise and maintain the living system. The hypothesis will be validated by achieving five key aims. Hydrogels with dual (electronic and ionic) conductivity will be created by combining organic conductor and biomacromolecule building blocks. A tailored additive microfabrication method will be developed to combine hydrogels in devices. Devices that transduce electronic commands into ionic currents, release/sequestration of signalling molecules and mechanical actuation (and vice versa) will be constructed. Devices will be integrated in arrays and in circuits capable of sensing and actuation in aqueous environments. Finally, an impact case study interfacing GELECTRO machines with cortical organoid cultures will be developed. By emulating the finely tuned morphogens present in the early stages of brain development, GELECTRO machines will encode advanced tissue organisation and emergent electrical activity in the organoids. The project will catalyse interest in hydrogel-based electronics as a promising technology for next generation human-machine interfaces.

Keywords: organic bioelectronics,electrodes,sensor arrays,conductive hydrogels,3d printing
Applying ARtificial Intelligence to Define clinical trajectorieS for personalized predicTiOn and early deTEctiOn of comorbidiTy and muLtimorbidiTy pattErnS (ARISTOTELES)

Framework: Horizon Europe — Global Challenges and European Industrial Competitiveness
Programme: Health
Theme: Health
Destination: Staying Healthy in a rapidly changing society
Action type: Research and Innovation actions
Countries involved: Italy,Denmark,Spain,Belgium,Norway,Romania,Greece,France,Portugal,United Kingdom
Call: Trustworthy artificial intelligence (AI) tools to predict the risk of chronic non-communicable diseases and/or their progression (HORIZON-HLTH-2022-STAYHLTH-01-two-stage, 2022)
Start date: 2023-11-01
End date: 2028-10-31
Duration (months): 60.0
Total project cost (EUR): 4093462.5
EU funding (EUR): 4093462.5
Participants: 18
Project status: SIGNED

The ARISTOTELES project aims to build a multinational harmonized data platform to develop and implement novel artificial intelligence (AI) approaches for management of complex diseases, where progression and manifestations of comorbidities are via multiple interacting pathways. We aim to apply our novel approach to a population of great need due to atrial fibrillation (AF), but our outputs can be extended to other complex diseases with multimorbidity. By integrating AIs into clinical practice, our platform will form a backbone for acceptable, responsible, and respectful uses of patient/participant data to develop and validate novel trustworthy AI tools for more personalized risk assessment and management. This represents a paradigm shift in AF treatment, moving from a focus on individual risk factors and selected outcomes (eg. stroke) to a holistic approach, underpinning timely diagnostic and therapeutic interventions to reduce disease progression, disability, hospitalizations and mortality, as well as improve patient adherence to lifestyle modifications, medications, and other treatment regimens. ARISTOTELES will be delivered through 8 inter-linking work-packages (WPs): WP1 is study management/coordination. WP2 provides the ethical/legal requirements for the development of a trustworthy AI. WP3 addresses stakeholder understanding of AI, needs assessment, and engagement in all the phases of the AI development. In WP4, granular data on genotype and phenotype characteristics, are harmonized from different datasets into a common platform. In WP5, AI algorithms/tools are developed and connected to an interactive output interface for patients and clinicians. In WP6, we test the AI tool developed in WP5 in a clinical trial simulation (in silico trial). In WP7 a multicenter randomized trial runs across multiple countries including both primary care and secondary care. WP7 and WP8 drive the clinical implementation and dissemination of results.

Keywords: atrial fibrillation,co morbidities,patients engagement,personalized medicine
Perception of materials, objects and spaces through active EXPLORAtion (EXPLORA)

Framework: Horizon Europe — Excellent Science
Programme: Marie Skłodowska-Curie Actions (MSCA)
Theme: Marie Skłodowska-Curie
Destination: Doctoral Networks
Action type: Marie Skłodowska-Curie actions
Panel: Social Sciences and Humanities
Countries involved: Germany,Netherlands,Italy,United Kingdom,Türkiye,Finland,France,Czechia,Canada,Sweden,Japan
Call: MSCA Doctoral Networks 2024 (HORIZON-MSCA-2024-DN-01, 2024)
Start date: 2026-02-01
End date: 2030-01-31
Duration (months): 48.0
Total project cost (EUR): 4206728.88
EU funding (EUR): 4206728.88
Participants: 24
Project status: SIGNED

Exploratory behaviour lies at the core of human essence. Being confronted with novel terrain, materials, tools, or artistic creations, humans instinctively explore the unknown in order to acquire information about it, to make sense of it, to act on it, and to appreciate what is in front of them. This quest for understanding involves dynamic engagement like walking, observing, handling objects, and manipulating them to witness changes in sight, touch, or sound. Active exploration is pivotal in shaping our sensory experiences of the world. Yet, the mutual relationships between perceptual experiences and the dynamic structures of the multisensorial information generated by active exploration are still not well understood. This presents a significant scientific challenge in itself and for comprehending the human mind's workings in natural settings. It also negatively impacts the development of multisensory interactive technologies and the innovative design of immersive systems, as well as the modelling of intelligent adaptive behaviour, thereby affecting nearly every facet of our life, including healthcare, education, mobility, AI, robotics and culture. EXPLORA aims to uncover the mutual interactions between perceptual impacts and active exploration systematically, quantitatively, and empirically. We propose a paradigm shift, approaching perception of materials, objects, and space as dynamic interactions with complex ecological systems. Through our innovative, cross-sectoral, multi-disciplinary, and sustainable research and training programme, we aim to catalyse this shift, creating impact through transfer between science, engineering, design, arts and industry and by connecting multiple levels of STEAM (Science, Technology, Engineering, Arts, and Mathematics) education from middle schools to doctoral education to enhance talent and knowledge circulation across the European R&I (Research and Innovation) landscape.

Keywords: active exploration,multi sensory perception,material,object and space perception,ecological psychology,cognitive,social,and cultural aspects in perception,
Towards an Artificial Cognitive Science (TACOS)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting grants
Action type: ERC actions
Panel: Computer Science and Informatics
Panel description: Informatics and information systems, computer science, scientific computing, intelligent systems
Countries involved: Germany
Call: ERC STARTING GRANTS (ERC-2023-STG, 2023)
Start date: 2024-01-01
End date: 2028-12-31
Duration (months): 60.0
Total project cost (EUR): 1496000.0
EU funding (EUR): 1496000.0
Participants: 1
Project status: SIGNED

With the advent of capable artificial agents comes the urgency to improve our understanding of how they learn, reason, and decide. This proposal aims to shape a new field of artificial cognitive science in which tools from cognitive psychology are used to understand and improve the behavior of the notoriously opaque artificial agents to which we increasingly delegate autonomy and authority. We will focus on the newly-emerged, disruptive, and increasingly powerful foundation models, huge neural networks with billion of parameters that are trained on hundreds of billions of words, and study them using tools from cognitive psychology. We will subject these models to experimental paradigms from the psychological literature and analyze their trial-by-trial behavior using detailed computational modeling. Psychological paradigms have been engineered to uncover precisely the mechanisms that underpin behavior. We will use cognitive psychology to study and improve prompt engineering, i.e. the design of textual inputs to these models that lead to a desired behavior. Afterward, we will build large cognitive benchmarks to assess foundation models' learning, decision-making, and reasoning abilities in both the pure language and the combined language and vision domains. Finally, we will attempt to improve these models' behavior using cognitive therapy. This proposal will help to create transparent and human-like agents and define an innovative and interdisciplinary research field in which cognitive psychologists and artificial intelligence researchers jointly examine and improve intelligent systems.

Keywords: foundation models,cognitive psychology,explainability
Nonlinear metasurfaces with 2D materials: Exploring their properties utilizing quasinormal modes (QUARTE)

Framework: Horizon Europe — Excellent Science
Programme: Marie Skłodowska-Curie Actions (MSCA)
Theme: Marie Skłodowska-Curie
Destination: Postdoctoral Fellowships
Action type: Marie Skłodowska-Curie actions
Panel: Physics
Countries involved: France
Call: MSCA Postdoctoral Fellowships 2023 (HORIZON-MSCA-2023-PF-01, 2023)
Start date: 2024-11-01
End date: 2026-10-31
Duration (months): 24.0
Total project cost (EUR): 211754.88
EU funding (EUR): 211754.88
Participants: 1
Project status: SIGNED

The regular rising demand for faster wireless communication (i.e., larger spectral bandwidths) was anomalously boosted recently due to the change on working habits of the Europeans who nowadays more and more work from home or become digital nomads. Optical metasurfaces offer this required high bandwidth combining it with easy fabrication, flexibility, and advanced functionality, rendering them a potential candidate to encounter this demand in wireless optical communications. Despite their large application span (wavefront manipulation, beam steering, perfect absorption), the design of optical metasurfaces is sometimes counter-intuitive and computationally cumbersome, especially when more advanced functionalities are targeted (nonlinear/all-optical control), typically realized by resorting to contemporary material options such as the 2D materials platform. QUARTE aims to present a coherent modal computational framework for the analysis and design of linear and, importantly, nonlinear metasurfaces realized with 2D materials, demonstrating advanced functionalities and all-optical control. The proposed modal framework, based on the concept of quasinormal modes (i.e., the natural modes of leaky and lossy cavities), will be capable of efficiently handling periodic systems (metasurfaces, gratings) consisting of 2D materials and possessing linear and, importantly, nonlinear responses and functionalities. Furthermore, as a modal technique, the proposed approach is capable of revealing the true physics that govern light-matter interaction, especially in the more obscure nonlinear regime, allowing for fast, efficient, and optimal designs with physical intuition and understanding of the involved physics and interactions. The realization of QUARTE research targets will be performed by the Researcher in the Laboratoire Photonique, Numérique et Nanosciences (LP2N), a Joint Research Unit of Centre National de la Researche Scientifique (CNRS).

Keywords: quasi normal modes,nonlinear photonics,metamaterials,metasurfaces,nonlinear metasurfaces,gratings,2d materials,periodic structures
Novel AI-Driven Fashion-Specific Recommendation Engine for Sustainable E-Commerce: Achieving 10% Return Reduction and >5% Gross Profit Increase (Dresslife 3R)

Framework: Horizon Europe — Innovative Europe
Programme: The European Innovation Council (EIC)
Theme: EIC Accelerator
Destination: Other destinations
Action type: EIC actions
Countries involved: Germany
Call: EIC Accelerator 2024 - Short application (HORIZON-EIC-2024-ACCELERATOR-01, 2024)
Duration (months): 24.0
Total project cost (EUR): 2160000.0
EU funding (EUR): 2160000.0
Participants: 1
Project status: SIGNED

Fashion e-commerce suffers from high return rates (6-16 times above other segments) and overstock-related revenue losses (each +€100B/y globally). Those problems result from unsolved fashion-specific complexities such as the highly personal clothing fit and shorter product life cycles (for fashion: 2 weeks, other segments: 3 months vs >3-5 years), which caused previous recommendation engines (RE) to fail. Dresslife developed a novel AI-Driven fashion-specific Recommendation Engine for sustainable E-Commerce achieving 10% return reduction and >5% gross profit increase for fashion retailers: the first comprehensive solution that solves the fashion-specific challenges. Our AI-based plug & play RE solves 3 essential challenges of clothing online sales: >5% gross profit increase by helping customers find clothing faster; 10% return reduction by improving size recommendations for an individual product and utilizing extensive clothing data; 50% less overstock by enabling >12-months demand prediction. With our SaaS business model, we target the global e-commerce apparel market (TAM), having a current size of ~€687.5B and showing a CAGR of 8.6%. Europe has the biggest market share of the e-commerce apparel market of Europe. Dresslife focuses on the AI in fashion market, our SAM, growing at a CAGR of 36.9% with a current market size of ~€1.6B and the size of our early addressable market being €301.5M. MOreover, we make a positive contribution to a more sustainable fashion industry by our approach who synchronizes sustainability with profitability. We see an important contribution to the protection of the environment and more sustainable e-commerce, including circular approaches to critical raw materials with our breakthrough innovation. We help to build a climate-neutral, green, fair, and social Europe reducing CO2 emissions trough a 10% reduction of return orders.

Keywords: fashion,prediction,ai,demand prediction,fit optimisation,personalised recommendation,product resorting,return avoidance,overstock mitigation,sustainability,graph neural networks
Point of care diagnostic solution for definitive differentiation of true and false threatened preterm labour cases (FineBirth)

Framework: Horizon Europe — Innovative Europe
Programme: The European Innovation Council (EIC)
Theme: EIC Accelerator
Destination: Open to supporting projects in all areas of science, technology,...
Action type: EIC actions
Countries involved: Spain
Call: EIC Accelerator Open (HORIZON-EIC-2022-ACCELERATOR-01, 2022)
Start date: 2023-04-01
End date: 2026-03-31
Duration (months): 36.0
Total project cost (EUR): 3346908.0
EU funding (EUR): 2342835.5
Participants: 1
Project status: SIGNED

Threatened Preterm Labour (TPTL) is the leading cause of preterm births and hospitalization during pregnancy. With 45M cases annually, treatments and resources are not being properly allocated towards the patients who need them. Efficient diagnosis of TPTL is the key to optimizing treatments but, current methods are ineffective at detecting true events. INNITIUS has developed Fine Birth, the first non-invasive PoC diagnostic device that uses torsional waves and AI to directly measure a patient’s cervical tissue consistency to identify the risk of TPTL in real-time. It is objective, accurate, fast and can be operated by staff with minimal training. We have reached TRL6, testing the prototype in a multicentre clinical study with +300 patients in 7 sites. We need €2.5M to fully develop and validate our AI software, do a multicentre pivotal clinical trial, and obtain regulatory approval, which we will be able to finalise with the support of the EIC.

Keywords: threatened preterm labour,premature births,machine learning,statistical data processing,medical device,torsional waves elastography,artificial intelligence,pregnancy,neonatal
The Generations and Gender Programme Preparatory Phase Project (GGP-5D)

Framework: Horizon Europe — Excellent Science
Programme: Research infrastructures
Theme: Research infrastructures
Destination: Development and infrastructures
Action type: Coordination and support actions
Countries involved: Netherlands,France,Poland,Germany,Hungary,Italy,Austria,Croatia,Czechia,Estonia,Lithuania,Norway,Spain,Sweden
Call: Preparatory phase of new ESFRI research infrastructure projects (HORIZON-INFRA-2021-DEV-02, 2021)
Start date: 2022-10-01
End date: 2026-09-30
Duration (months): 48.0
Total project cost (EUR): 2999997.5
EU funding (EUR): 2999997.5
Participants: 15
Project status: SIGNED

The Generations and Gender Programme (GGP) is an interdisciplinary research infrastructure on population and family dynamics. It collects, processes and disseminates cross-nationally comparable longitudinal data on young adults, families, generational exchanges, and the life courses of women and men. It is the only RI focused on answering the key scientific and societal challenges related to the causes consequences of demographic changes. The main objective of the GGP-5D project is to enhance the long-term sustainability of the RI (research infrastructure) with a view towards establishing it as a permanent one with its own legal entity. To achieve this, the GGP-5D project will work on enhancing five dimensions: (1) Technical excellence, (2) Scientific and socio-economic impact and engagement, (3) Financial sustainability, (4) Legal frameworks, and (5) Positioning in the landscape of RIs. Together these five dimensions are expected to contribute to the excellence and attractiveness of the European Research Area in the field of population studies, to provide a solid ground for investment in the GGP, and to result in a well-functioning ecosystem of social sciences RIs.

Keywords: demographic changes,survey,longitudinal,cross national