Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Reconfigurable Intelligent Surface-Assisted VLC for battery-free IoT devices (RISA-VLC)

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: Information Science and Engineering
Countries involved: Spain,United States
Call: MSCA Postdoctoral Fellowships 2021 (HORIZON-MSCA-2021-PF-01, 2021)
Start date: 2023-01-01
End date: 2025-12-31
Duration (months): 36.0
Total project cost (EUR): 261380.64
EU funding (EUR): 261380.64
Participants: 2
Project status: CLOSED

The vast development of smart communication devices for the Internet of Things (IoT) is incurring an ever-increasing demand of wireless data services and energy sources. It is expected to witness a growth of connected IoT devices in the next few years, reaching up to tens of billions. Currently, these devices rely on batteries for its operation, but the battery recycling is a delicate matter that has a negative environmental impact due to their chemical components. Thus, it is reasonable to think that future communication systems must comply with energy-efficiency standards by minimizing the use of batteries, and then reduce its carbon footprint. The main objective of RISA-VLC is to enable battery-free IoT devices by engineering, thanks to reflective intelligent surfaces (RIS), the propagation channel of the Visible Light Communication (VLC) technology. To this end, I will retrofit the pervasive deployment of indoor LEDs to provide a robust communication link and an enhanced light power received at IoT devices. In the outgoing phase at University of Virginia I will characterize RIS to perform the additional channel path, which I will also model. Then, I will study its effect in the communication and lighting performance. In the return phase at the Universidad Carlos III de Madrid I will research novel signal-processing and communication techniques to exploit the manageable channel proposed during the outgoing phase. Besides, I will establish guidelines for creating battery-free VLC-enabled IoT devices. The training activities proposed are fundamental for the achievement of RISA-VLC and my personal career goals. RISA-VLC guarantees a three-way transfer of knowledge since it combines my past experience in theoretical VLC techniques and VLC prototyping, with supervisors' expertise on optimization of systems, VLC reflection exploitation and advanced signal processing and communication techniques.

Keywords: visible light communication,reconfigurable intelligent surfaces,energy harvesting,line of sight link blockage
Support Utilisation of Sustainable and TAilored INnovative methods for HTA (SUSTAIN-HTA)

Framework: Horizon Europe — Global Challenges and European Industrial Competitiveness
Programme: Health
Theme: Health
Destination: Maintaining an innovative, sustainable and globally competitive health industry
Action type: Coordination and support actions
Countries involved: Netherlands,Italy,Spain,Norway,United Kingdom,Hungary
Call: Supporting the uptake of innovative Health Technology Assessment (HTA) methodology and advancing HTA expertise across EU (HORIZON-HLTH-2023-IND-06, 2023)
Start date: 2024-01-01
End date: 2027-12-31
Duration (months): 48.0
Total project cost (EUR): 4488718.75
EU funding (EUR): 4488718.75
Participants: 15
Project status: SIGNED

With ever-increasing complexity of novel health technologies, Health Technology Assessment (HTA) methodologies have been evolving rapidly. However, there is now a lack of harmonization on the methodological needs of HTA bodies against the varied methodologies and tools. There is a need for a solution that allows for continuous dialogue between HTA bodies and academia, a solid, unified base for implementation of fit-for-purpose methodologies and long-term upskilling on HTA expertise. SUSTAIN-HTA aims to upskill the pan-European HTA body workforce and harmonise HTA expertise via a robust education and training framework that ensures continuous uptake of novel, need-based HTA methodologies. Aligned to the methodological developments as part of the new EU HTA regulation, the project will set up a mechanism for dialogues and interaction between HTA bodies and academia to regularly assess HTA-bodies’ needs in parallel with a methods observatory that ensures up-to-date knowledge of latest HTA methods. Prioritized methods will be piloted within HTA bodies and, after endorsement, implementation will be supported by a harmonized training and education framework that will be established to upskill the HTA experts. A long-term dissemination and communication structure among all stakeholders will be established to guarantee a feedback loop between HTA needs, methods assessment and associated training needs. Via the collaboration of 5 universities, 7 HTA bodies, 2 SMEs and one non-profit organization, SUSTAIN-HTA brings together extensive experience in (coordinating) previous European funded HTA-related projects including HTx, EHDEN, COMED and GetReEal. With this, SUSTAIN-HTA has the background for establishing sustainable business models that ensures continuity of project outcomes and activities in years beyond the project. SUSTAIN-HTA will support European leadership in the HTA field reach HTA bodies across at least 15 European countries with hundreds of people upskilled.
Reinventing Multiterminal Coding for Intelligent Machines (IONIAN)

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: Belgium
Call: ERC CONSOLIDATOR GRANTS (ERC-2024-COG, 2024)
Start date: 2025-06-01
End date: 2030-05-31
Duration (months): 60.0
Total project cost (EUR): 1999403.75
EU funding (EUR): 1999403.75
Participants: 1
Project status: SIGNED

Advancements in sensors and deep learning have elevated the perception capacity of machines, bringing mid-level autonomy within reach. However, the abundance of high-dimensional data, including video and dynamic point cloud streams, strains current storage and communication technologies to their limits and curtails the ability of machines to collaboratively perceive the environment, a critical factor for achieving safety and the ambitious goal of high-level autonomy. State-of-the-art cooperative perception methods are based purely on a data-driven approach, requiring massive training data and computational resources, and lacking interpretability, explainability, and a solid theoretical foundation. This proposal puts forth a groundbreaking multiterminal coding paradigm for intelligent machines enabling data compression and communication systems that break the current limits of the predictive coding archetype. It builds a unique concept that unifies traditional distributed source coding and signal processing domain knowledge with modern deep learning. First, it leverages machine learning to solve long-standing problems in multiterminal coding theory and devise code constructions achieving the fundamental limits, thereby establishing a theoretical framework that defines the amount of information required to be sent per agent to solve the cooperative perception task. Second, it leverages domain knowledge to drive the design of interpretable and data- and parameter-efficient machine learning models for cooperative perception. Third, it reinforces this interplay by pioneering explanations that enforce and assess the interpretability of the designed models. IONIAN will have a profound impact on the way intelligent machines, including ground and aerial vehicles, and mobile robots, compress and communicate multi-sensory data to collaboratively perceive the environment for autonomous safe navigation, ultimately leading to trustworthy operation and acceptance of such systems.

Keywords: machine learning for signal processing,cooperative perception,distributed source coding,distributed video coding,multiterninal source coding,video and point cloud processing,multimedia communications,smart transportation systems,autonomous vehicles,intelligent machines
Multiscale Imaging of Cardiovascular Pressure Gradients – a Paradigm Shift in Hemodynamic Risk Prediction (MultiPRESS)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting grants
Action type: ERC actions
Panel: Prevention,  Diagnosis and T reatment 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 STARTING GRANTS (ERC-2022-STG, 2022)
Start date: 2023-05-01
End date: 2028-04-30
Duration (months): 60.0
Total project cost (EUR): 1621913.0
EU funding (EUR): 1621913.0
Participants: 1
Project status: SIGNED

Regional quantification of cardiovascular pressure gradients is critical for diagnosis, treatment planning, and risk prediction of many cardiovascular diseases. Still, for a large number of conditions, non-invasive assessment is obstructed by inherent method limitations, and a wide range of cardiovascular instances exist where regional pressure behaviour remains unexplored. The MultiPRESS project main objective is to develop a novel imaging paradigm for non-invasive assessment of cardiovascular pressure gradients, overcoming critical limitations of existing techniques through a unique multiscale approach. Doing so, the MultiPRESS project seeks to – for the first time – extend non-invasive hemodynamic risk prediction into previously inaccessible cardiovascular domains, advance our knowledge of complex hemodynamic behaviour, and tackle remaining urgent clinical challenges across the heart, aorta, and brain. Using deep integration of advanced full-field magnetic resonance imaging (4D Flow MRI), super-resolution networks, and physics-informed image processing, a set of core developments will allow for unique, comprehensive image-based pressure gradient assessment across (1) spatial (big/small vessels), (2) temporal (fast/slow flows), and (3) flow (laminar/turbulent) scales, with developments consistently validated in dedicated in-silico, in-vitro, and in-vivo cohorts. These developments will then be utilized on a set of core applications across (4) cardiovascular scales (heart/aorta/brain), addressing urgent clinical challenges and extending image-based pressure gradient quantification through previously inaccessible domains. Based in a unique multidisciplinary setting at Scandinavia’s largest university hospital, successful delivery of MultiPRESS will represent a paradigm shift in clinical hemodynamic risk prediction, and pave way for new scientific knowledge revitalizing risk stratification of complex cardiovascular disease across the heart, aorta, and brain.

Keywords: cardiovascular imaging,magnetic resonance imaging,hemodynamics,pressure gradients,super resolution machine learning
Strengthening the Capacity of Excellence Hubs of Türkiye, Greece, and Ukraine to Support Innovation Ecosystem of Novel Foods Based on Plant Proteins (Excel4Pro)

Framework: Horizon Europe — Widening Participation and Strengthening the European Research Area
Programme: Widening participation and spreading excellence
Theme: Improved access to Excellence
Destination: Improved access to Excellence
Action type: Coordination and support actions
Panel: Chemistry
Countries involved: Türkiye,Greece,Ukraine,Belgium
Call: Excellence Hubs (HORIZON-WIDERA-2023-ACCESS-07, 2023)
Start date: 2025-01-01
End date: 2028-12-31
Duration (months): 48.0
Total project cost (EUR): 5946368.75
EU funding (EUR): 5946368.75
Participants: 17
Project status: SIGNED

Three key global drivers underpin the increased interest in plant protein-based diets: population-growth, important role of proteins in a healthy diet, and the environmental impact of animal-based food chains. While an increasing trend in proportion of plant sources included in diet is obvious, the current generation of commercial plant-based alternatives is suboptimal. Therefore, more research is needed to develop mild processing techniques for plant proteins and to obtain a comprehensive understanding on the impact of plant proteins on technological and nutritional functionality. Addressing current challenges and shortcomings, Excel4Pro aims to support, with underpinning research and knowledge exchange, the capacity of the national Excellence Hubs of Türkiye, Greece, and Ukraine as a regional launch pad for plant-protein-based novel food economies. Excel4Pro will be used as a critical tool to connect and scale up the strategically selected plant-based protein ecosystems in a single, interconnected and cross-border Excellence Hub dedicated to growing and changing the agri-food sector in Türkiye, Greece and Ukraine by developing novel food products based on plant-based proteins. Collaborative R&I strategies, mentoring programmes, action plans to attract dedicated investment, and an array of upskilling activities for researchers and entrepreneurs will help close knowledge gaps between place-based innovation ecosystems and support the development of more sustainable food systems. Excel4Pro's consortium contains 17 partners (4 Academic, 8 Business, 2 Public Authorities, and 3 Societal Actors) that are well balanced and fully completes the quadruple helix. Excel4Pro is a 4 years project with 6 carefully designed Work Packages that efficiently exploit the consortium's diverse knowledge and expertise to develop solutions to Global Challenges in line with EUGreen Deal, the Farm to fork strategy for a fair, healthy and environment-friendly food system.

Keywords: plant proteins for food,protein diversification,green deal
Pushing the Limit of Aerosol Nanoscale Engineering with Tiny nanoparticles (PLANET)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Advanced grants
Action type: ERC actions
Panel: Products and Processes Engineering
Panel description: Product and process design, chemical, civil, environmental, mechanical, vehicle engineering, energy processes and relevant computational methods
Countries involved: Greece
Call: ERC ADVANCED GRANTS (ERC-2024-ADG, 2024)
Start date: 2026-01-01
End date: 2030-12-31
Duration (months): 60.0
Total project cost (EUR): 3498333.0
EU funding (EUR): 3498333.0
Participants: 1
Project status: SIGNED

In gas-phase manufacture of materials as well as in the atmosphere, the interaction between gas molecules and tiny nanoparticles (TNPs, i.e. particles having sizes from ca. 0.5 to 5 nm) determines their characteristics. These are crucial for the environment impact (climate, air quality and visibility) of TNPs and their performance in engineering and life science applications. Will two molecules collide and go their ways or stick to form a TNP that will grow to a nanoparticle (NP; i.e., a particle from 5 to 100 nm in size) of desired crystallinity? Today manufacturing of NPs is well understood, even at tons/hour (i.e. fumed oxides). However, for TNPs that hold most of the promises of nanotechnology, there is much uncertainty that hinders quantitative understanding of their formation, growth and transport and subsequently the systematic process design for their manufacturing. This project aims at advancing the fundamentals of aerosols from the sub-nano to the few nm scale through methodical experiments and comparison to state-of-the-art molecular dynamics simulations. It will capitalize on a 2023 discovery regarding the exact nature of gas collisions (from ballistic to orbiting and multi-body ones) that nearly halves the well-established value of the gas mean free path that defines aerosol dynamics in the free molecule or the continuum regime. This understanding will be reduced to easy-to-use expressions for process design at the lowest and most potent nanosize range. Project objectives are to: a) explore the interactions of gas molecules with TNPs by fully accounting for the precise structure and force fields of both entities, b) generate TNPs by spark ablation and measure their transport properties, c) develop a nucleation rate of TNPs accounting for the above interactions and d) place on a firm scientific basis the dynamics of aerosol TNPs bridging the gap between molecules and larger (> 5 nm) particles for material synthesis and even atmospheric airshed modeling.

Keywords: aerosol nanoparticles,molecular dynamics,particle technology,aerosol diffusion,aerosol nucleation,aerosol coagulation,aerosol engineering
Making our food safety control system greener (GreenFOCUS)

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: Chemistry
Countries involved: Netherlands,Greece
Call: MSCA Postdoctoral Fellowships 2024 (HORIZON-MSCA-2024-PF-01, 2024)
Start date: 2026-01-15
End date: 2028-01-14
Duration (months): 24.0
Total project cost (EUR): 217076.16
EU funding (EUR): 217076.16
Participants: 2
Project status: SIGNED

Food safety is still a challenge considering climate change and growing global population. Human exposure to contaminated food lead to numerous health risks including foodborne and chronic diseases. Natural toxins such as mycotoxins, plant toxins, and phytotoxins, play a significant role in food contamination, causing substantial losses in the agriculture and aquaculture sectors. Additionally, their co-occurrence in food samples together with the potential presence of masked or unexpected toxins can have synergistic and unknown toxic effects, posing emerging risks to human health. Current analytical methods to monitor these contaminants require high consume of hazardous organic solvents and generate significant waste, having a considerable environmental impact. Furthermore, most standard protocols target a limited range of compounds, reducing the scope of the analysis. GreenFOCUS aims to develop a sustainable, green analytical methodology for detecting multiple classes of natural toxins in food and food supplements. The project proposes the use of eco-friendly solvents to replace harmful organic solvents and biodegradable materials to reduce plastic waste. Advanced analytical techniques such as cyclic ion mobility coupled to high-resolution mass spectrometry will be explored to reduce total time of analysis and to expand the detection scope using non-target and suspect screening workflows. The development of a new metric tool (Eco-GATE) considering green, white and circular analytical chemistry will allow to assess the greenness and transferability of analytical methods, aiming to develop and implement sustainable methodologies in food analysis. The method will be validated in European reference laboratories and within the food industry to demonstrate its real-word applicability. In general, GreenFOCUS aims to transform food safety systems across public and private sectors, ensuring a safer and more sustainable future for food systems.

Keywords: green analytical chemistry,food safety,food analysis,natural toxins,green solvents,food supplements,non target screening,circular analytical chemistry
distributed ledger technologies and user-driven automation towards self-SOVEREIGN mobile data access in beyond 5G networks (SOVEREIGN)

Framework: Horizon Europe — Excellent Science
Programme: Marie Skłodowska-Curie Actions (MSCA)
Theme: Marie Skłodowska-Curie
Destination: Staff Exchanges
Action type: Marie Skłodowska-Curie actions
Panel: Information Science and Engineering
Countries involved: Greece,Sweden,Portugal,Luxembourg,Romania,Spain
Call: MSCA Staff Exchanges 2022 (HORIZON-MSCA-2022-SE-01, 2022)
Start date: 2024-01-01
End date: 2027-12-31
Duration (months): 48.0
Total project cost (EUR): 2026628.57
EU funding (EUR): 1656000.0
Participants: 8
Project status: SIGNED

Towards the forthcoming transition to a fully connected world (e.g., Internet of Senses, digital twins), support of connected intelligence requires service advertisement, discovery, negotiation and management that goes beyond the complexity and scalability that existing technologies and subscription-driven MNO processes can handle. In Beyond 5G (B5G) networks, cyber-physical assets and intelligent end points will be capable of translating current service requirements to comprehensive technical specifications dynamically (e.g., QoS/QoE management per service chunk) as well as request for full customization of their service terms in line with current availability of tenants/resources and their application requirements. Distributed ledger technologies (DLTs) hold the key for natively disintermediated, cost-efficient, and anonymous B5G communications, enabling transparency and trust to be established across the integrated DLT, radio access and core network continuum. The SOVEREIGN research programme aims to fuel artificial intelligence (AI) with DLT-backed data in order to innovate the B5G service chain and the B5G protocol stack towards the support of fully decentralized, instantaneous, and anonymous resource trading across the B5G network ecosystem (end terminals, infrastructure, OTT service providers, etc.). SOVEREIGN aims to empower intelligent end points in B5G networks, to gain full control of their identities, connectivity, sessions, service terms, and shared data upon accessing B5G spectrum, antennas, network slices and services. To this end, SOVEREIGN will conceptualize and develop a modular end-to-end service architecture integrating DLT-empowered service provisioning, fully decentralized AAA operations, forward-thinking protocols for self-sovereign identity management and anonymity/data privacy preservation as well as user-driven AI-enabled mobility management and traffic steering over joint DLT/B5G system infrastructures.

Keywords: mobile data networks,distributed ledger technologies,network automation,self sovereign access,network security