Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
ENERSENS Motion to Thin Insulation (EN.MOTION)

Framework: Horizon Europe — Innovative Europe
Programme: The European Innovation Council (EIC)
Theme: EIC Accelerator
Destination: Challenges
Action type: EIC actions
Countries involved: France
Call: Green Deal innovations for the Economic Recovery (HORIZON-EIC-2021-ACCELERATORCHALLENGES-01, 2021)
Start date: 2022-02-01
End date: 2025-05-31
Duration (months): 40.0
Total project cost (EUR): 3468278.5
EU funding (EUR): 2427794.0
Participants: 1
Project status: CLOSED

With the impact of building and transport activities on the environment becoming more and more apparent, thermal insulation materials are being widely used to increase energy efficiency and cleanliness ─ via renovation in buildings, development of EV and associated batteries. Several conventional insulation materials exist. But a new generation of high-performance insulation based on silica aerogel advanced materials are about to revolutionise the market. But the problem lies in the production cost of silica aerogel materials, too expensive to be adopted at large scale and too complex to meet the markets’ size requirements. ENERSENS has developed EN.MOTION: a continuous manufacturing process to create cost-efficient, ready to use, 3x more performant, ultra-thin film aerogel blankets (SKOGAR®). With EN.MOTION, ENERSENS has the ambition to become the leader of high-performance insulation material thanks to an innovative industrial process that reduces drastically the production costs.

Keywords: aerogel,sustainable,cost efficient,ultra thin,electric vehicles,building,insulation material,silica based aerogel,manufacturing process
First autofocus eyewear to offer perfect vision for people with multiple and progressing vision problems (Perfect Vision)

Framework: Horizon Europe — Innovative Europe
Programme: The European Innovation Council (EIC)
Theme: EIC Accelerator
Destination: Other destinations
Action type: EIC actions
Countries involved: Finland
Call: EIC Accelerator 2024 - Short application (HORIZON-EIC-2024-ACCELERATOR-01, 2024)
Duration (months): 24.0
Total project cost (EUR): 2500000.0
EU funding (EUR): 2500000.0
Participants: 1
Project status: SIGNED

Eyesight is our most critical sense providing over 80% of our sensory impressions, but in the modern world people’s eyesight has become significantly worse. It is the result of irreversible megatrends of increasing indoor lifestyle with high use of digital devices and aging population. While the former affects the development of young eye causing shortsightedness, then population aging leads to higher prevalence of inevitable aging related farsightedness. Moreover, with an aging population, economies increasingly rely on an aging workforce among whom the prevalence of both vision problems is continuously expanding. To prevent this problem from weighing down people’s productivity as well as their personal wellbeing, Pixieray introduces breakthrough autofocus eyewear technology to effectively provide perfect vision for those whose eyes are naturally not up to it anymore. While progressive eyewear with static lenses is currently the primary remedy for correcting near and far sight vision, they severely limit field of clear vision for different distances, create peripheral vision distortions and cause physical discomfort through dizziness and neck strain. In contrast, Pixieray combines its proprietary liquid crystal lens and world’s smallest and power efficient IR based eye tracking technologies to dynamically adjust eyewear’s optical power given the user’s viewing distance and prescription strength. This allows the wearer to see clearly at every distance with full field of vision and without distortions and physical discomfort.

Keywords: autofocus eyewear,tunable liquid crystal lens,ir eye tracking,neural networks,myopia,presbyopia
Clinical Development of KP405, a First-in-Class Neuroprotective Drug to Slow Parkinsons’s Disease Progression (NEURO-SHIELD)

Framework: Horizon Europe — Innovative Europe
Programme: The European Innovation Council (EIC)
Theme: EIC Accelerator
Destination: Other destinations
Action type: EIC actions
Countries involved: Denmark
Call: EIC Accelerator 2024 - Short application (HORIZON-EIC-2024-ACCELERATOR-01, 2024)
Duration (months): 42.0
Total project cost (EUR): 2500000.0
EU funding (EUR): 2500000.0
Participants: 1
Project status: SIGNED

Kariya Pharmaceuticals (Kariya) is developing KP405, a novel, brain-permeable, first-in-class dual GLP-1/GIP receptor agonist for the treatment of Parkinson’s disease (PD). PD is the second most common neurodegenerative disease worldwide, currently affecting over 10M people. To date, there is no disease-modifying therapeutic available on the market. The current standard of care solely relies on symptomatic treatments that fail to stop the loss of dopaminergic neurons, leading to progressive decline in the patients’ motor functions. The severity of the symptoms, especially at advanced disease stages, profoundly impacts the patients’ quality of life. Thus, there is a clear unmet medical need to develop a novel disease-modifying agent that effectively slows the progression of PD. While incretin hormones such as GLP-1 and GIP are currently approved for the treatment of type 2 diabetes, they also possess neuroprotective properties, and their positive clinical effects have already been demonstrated in PD patients. However, these diabetes drugs have all lost patent exclusivity, and as such, pharmaceutical companies are not commercially incentivized to invest in the costly development of these compounds for PD, despite their promising efficacy. As a differentiated, patent-protected drug, our lead asset KP405 thus has the potential to significantly disrupt the PD treatment market and become a multi-blockbuster drug. With the Phase 1 clinical trial for KP405 commencing in 2024, the NEURO-SHIELD project aims to, in parallel, prepare KP405 for the Phase 2 clinical trial, which will subsequently be conducted following positive evaluation of the Phase 1 results. Completion of the Phase 2 program will present a significant value inflection point for Kariya, which is anticipated to result in a strategic partnership for the final development and commercialization of KP405. Thereby, Kariya will be able to become self-sufficient and invest in advancing its pipeline.

Keywords: neurodegenerative disease,parkinson s disease,disease modifying drug,stalling disease progression,dual incretin analogue,glp 1,gip,receptor agonist,blood brain barrier,central nervous system
Industrial scale miRNA extraction technology and discovery platform to harness the power of plant miRNA (MIRNAgreen)

Framework: Horizon Europe — Innovative Europe
Programme: The European Innovation Council (EIC)
Theme: EIC Accelerator
Destination: Other destinations
Action type: EIC actions
Countries involved: Italy
Call: EIC Accelerator 2025 - Short application (HORIZON-EIC-2025-ACCELERATOR-01, 2025)
Duration (months): 24.0
Total project cost (EUR): 2499999.0
EU funding (EUR): 2499999.0
Participants: 1
Project status: SIGNED

While single sequence microRNA (miRNA) finds application in few specialized sectors (e.g. therapeutics) thanks to its capability of regulating specific genes, plant miRNA exerts multi-faceted effects on plants, animals and humans, potentially finding application across a wider variety of industries including cosmeceuticals, nutraceuticals, agro and more. However, current plant miRNA extraction technology exploits the same complex and expensive lab-based technologies and toxic reagents used for extracting single sequence miRNA, hindering use of plant miRNA in these sectors. We developed and patented a technology that allows large scale and cost effective extraction of plant miRNA, using non-toxic reagents, which can be used for a variety of customers in a variety of fields to generate entirely new products. In this project we will demonstrate (directly with a prospect customers) application across a target vertical that we identified as most receptive towards our technlogy.

Keywords: plant microrna
Tech and business validation towards market readiness of high-performance PFSA-free intermetallic Pt-alloy membrane electrode assemblies for PEMFCs: Enabling next-gen hydrogen-based transport (ENABLER)

Framework: Horizon Europe — Innovative Europe
Programme: The European Innovation Council (EIC)
Theme: EIC Transition
Destination: Challenges
Action type: EIC actions
Countries involved: Slovenia,Germany
Call: EIC Transition Challenge: Process and system integration of clean energy technologies (HORIZON-EIC-2022-TRANSITION-01, 2022)
Start date: 2023-06-01
End date: 2025-11-30
Duration (months): 30.0
Total project cost (EUR): 2495900.0
EU funding (EUR): 2495900.0
Participants: 3
Project status: SIGNED

ENABLER’s final objectives are to assemble, demonstrate and test a proton exchange membrane fuel cell (PEMFC) short stack - functional energy generation device - with reduced platinum content (0.3 mgPt/cm2) and free of perfluorinated sulfonic acid (PFSA) compounds matching the performance of the current state-of-the-art PFSA-containing PEMFCs and, in parallel, to ensure market readiness for the technologies. The project will lay the foundation for more widespread exploitation of hydrogen power by enabling more efficient use of Pt as a critical raw material, providing improved performance and durability with advanced intermetallic Pt-alloy catalysts materials; achieving higher operating temperatures of PEMFCs (105 °C) by replacing conventional PFSA ionomers and membranes with novel hydrocarbon (HC) materials and, consequently removing the toxic perfluorinated compounds out of PEMFC manufacturing, resulting in positive effect on the economy and society. Thus, ENABLER’s long-term objective is to improve the commercial viability of PEMFC and ramp up its mass use to decarbonize transport and energy sectors. ENABLER will reach the tech objectives by designing a set of interrelated activities: (i) catalyst finetuning to ensure compatibility with the HC materials (ii) CCM production processes finetuning and CCM fabrication with advanced catalyst, HC membranes and ionomers integrated (iii) fabrication and validation of single cells and short stack. Business objectives will be achieved through market validation activities, performance of techno-economic and investment analysis as well as business plan creation and IPR management activities. The ENABLER consortium is designed to create a non-existing PFSA-free European value-chain requiring a minimum of critical resources - with ReCatalyst being responsible for catalyst, ionysis – CCM fabrication and EKPO – PEMFC technology. All partners will work on market readiness to ensure the value chain sustainability in the future.

Keywords: proton exchange membrane fuel cell,membrane electrode assembly,catalyst coated membrane,novel platinum alloy catalyst,hydrogen,heavy duty vehicles,short stack,value chain,market readiness
Using passive acoustic monitoring methods to survey birds communities in biodiverse agricultural farmlands in the EU (BIOMON)

Framework: Horizon Europe — Widening Participation and Strengthening the European Research Area
Programme: Widening participation and spreading excellence
Theme: Attracting and mobilising the best talents
Destination: Attracting and mobilising the best talents
Action type: Marie Skłodowska-Curie actions
Panel: Environment and Geosciences
Countries involved: Cyprus
Call: Fostering balanced brain circulation – ERA Fellowships (HORIZON-WIDERA-2022-TALENTS-02, 2022)
Start date: 2022-06-01
End date: 2024-05-31
Duration (months): 24.0
Total project cost (EUR): 148488.0
EU funding (EUR): 148488.0
Participants: 1
Project status: CLOSED

The European Union's Biodiversity Strategy for 2030 emphasizes the need to halt biodiversity loss driven by anthropogenic activities. However, to achieve this, it is necessary to understand how those activities affect biodiversity so that evidence-based conservation interventions can be made. Therefore, effective monitoring tools are needed that can be used to survey biodiversity changes over large spatial and temporal scales. Conventional monitoring tools, based on expert field surveys, are time-consuming and expensive and, therefore, inappropriate for such large-scale monitoring. Consequently, researchers worldwide are increasingly turning their attention to new technologies. When it comes to monitoring vocalizing animals, such as birds, which have been shown to be appropriate indicators of biodiversity, researchers focus on the use of passive acoustic monitoring methods. However, further development of those methods is needed before conservation practitioners can use them widely and reliably in the field to monitor bird communities. BIOMON's main objective is to extend the current state-of-the-art acoustic monitoring approaches through the novel use of machine learning techniques. BIOMON's overarching goal is to develop an innovative passive acoustic monitoring protocol that can be used to survey bird communities in biodiverse agricultural farmlands in the EU. The EU is home to many species of which the persistence depends on low-intensity agricultural areas, and consequently, developing appropriate monitoring tools for those areas remains a key research priority. The methods and monitoring protocol developed in BIOMON, through the collaboration of the ER, a conservation biologist, and the supervisor, a machine learning expert, have the potential to contribute to the objectives of the EU's Biodiversity Strategy for 2030 and other related policies such as the Common Agricultural Policy.

Keywords: acoustic indices bird monitoring bioacoustics machine learning soundscape ecology
COGSTIM: Online Computational Modulation of Visual Perception. (COGSTIM)

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: Life Sciences
Countries involved: Germany
Call: MSCA Postdoctoral Fellowships 2021 (HORIZON-MSCA-2021-PF-01, 2021)
Start date: 2023-02-01
End date: 2025-01-31
Duration (months): 24.0
Total project cost (EUR): 173847.36
EU funding (EUR): 173847.36
Participants: 1
Project status: CLOSED

Computational models of vision often address problems that have a single and definite end-point, such as visual recognition: an example of this might be to find a ripe banana in a complex scene. However, not all computation is of this form. Visual information is processed continuously in sensory areas and the nervous system has the capacity to alter or halt an ongoing behavioral response to changes in incoming information. We can therefore react flexibly to updated sensory input or changed requirements for motor output. On the other hand, these same neuronal mechanisms must also support perceptual stability, so that noisy signals do not cause loss of a crucial goal. In project COGSTIM, I will investigate the functional neuronal networks that support the balance between perceptual flexibility and stability, within primate visual areas. I will use a highly innovative approach, combining dense electrophysiological recording with online (real-time) decoding of neuronal correlates of the subject’s perceptual choice, based on adaptive machine-learning algorithms. In order to control visual perception effectively and predictably, closed-loop electrical stimulation will be applied under dynamically adjusted feedback to identified neuronal circuits that causally modulate associated percepts. Crucially, this novel approach using joint decoding and stimulation in real time will allow me to target dynamically visual percepts, representing a significant advance in our understanding of on-going, continuous computations of the primate brain. Such developments offer promising bases for the future development of rehabilitative therapeutical protocols, as well as innovative brain machine interfaces suitable for real-world use.

Keywords: visual perception,brain machine interface,electrophysiology,closed loop stimulation
High-dimensional nonparametric Bayesian causal inference (BayCause)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting grants
Action type: ERC actions
Panel: Mathematics
Panel description: All areas of mathematics, pure and applied, plus mathematical foundations of computer science, mathematical physics and statistics
Countries involved: Netherlands
Call: ERC STARTING GRANTS (ERC-2022-STG, 2022)
Start date: 2023-09-01
End date: 2028-08-31
Duration (months): 60.0
Total project cost (EUR): 1596136.25
EU funding (EUR): 1499770.0
Participants: 2
Project status: SIGNED

Causal conclusions are at the center of research, yet notoriously difficult to obtain. Many research studies report correlations only, which, in line with the maxim, do not imply causation. With correlations, one can make predictions. With causation, one can intervene. Paradoxically, causal inference can become harder when more data becomes available. In the by now increasingly common high-dimensional settings which are the focus of this proposal, including all variables is impossible while including too few can severely bias results. Variable selection becomes necessary, yet available methods are in short supply. My aim is to develop Bayesian nonparametric methods and theory for high-dimensional causal inference. Bayesian nonparametrics is eminently suited for variable selection in causal inference, because it excels at both incorporating and describing uncertainty. Recent theoretical advances, in particular in Bernstein-von Mises theory and high-dimensional nonparametric regression, have now finally opened up causal inference to Bayesian nonparametric approaches. I will investigate high-dimensional versions of the two most important causal frameworks, based on unconfoundedness and directed acyclic graphs. I will focus on novel aspects scarcely available in the literature, including uncertainty quantification, a broad range of data types, and nonlinear relationships. My expertise in causal inference, Bayesian nonparametrics, variable selection and survival analysis puts me in a unique position to work on this multifaceted challenge. My dual track in theoretical and applied statistics enables me to identify the problems which have highest priority in practice and are mathematically interesting. The novel methods with solid mathematical statistical foundation resulting from this proposal will tremendously expand the now limited settings in which trustworthy high-dimensional causal inference is possible, with applications in medicine, economics and many other fields.

Keywords: causal inference bayesian nonparametrics variable selection uncertainty quantification potential outcomes directed acyclic graphs survival analysis
Solid Basis for Symmetric Cryptography (SoBaSyC)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Consolidator grants
Action type: ERC actions
Panel: Computer Science and Informatics
Panel description: Informatics and information systems, computer science, scientific computing, intelligent systems
Countries involved: France
Call: ERC CONSOLIDATOR GRANTS (ERC-2023-COG, 2023)
Start date: 2024-04-01
End date: 2029-03-31
Duration (months): 60.0
Total project cost (EUR): 2000000.0
EU funding (EUR): 2000000.0
Participants: 2
Project status: SIGNED

Symmetric cryptography, essential for enabling secure communications, has benefited from an explosion of new results in the last two decades, in big part due to several standardization efforts: many public competitions have been launched since 1997, where the community proposes cryptographic constructions and simultaneously evaluates their security and performance. The security of symmetric cryptography is based on cryptanalysis: we only gain confidence in a symmetric cryptographic function through extensive and continuous scrutiny. However, the current context has not allowed the community to digest all the new findings, as can be seen from several recurrent issues. The two main ones are: 1) primitives proposed at top-tier venues often get broken by slight modifications of already known techniques; 2) published cryptanalysis at top conferences sometimes include mistakes or are suboptimal. They are also often re-invented and re-named. The main challenge of SoBaSyC is to establish solid bases for symmetric cryptography. Using cryptanalysis as the starting point, my aim is to unify the knowledge obtained through the years on the different families of attacks, to transform it with an algorithmic approach and to endow it with optimizations. The final result will be a toolbox congregating all our newly proposed optimized algorithms, that will provide the best known attacks on a given construction, through an easy application. Next, I plan to derive from this algorithmic approach some theoretical bounds, as well as some properties that I will include in the security proofs of symmetric constructions, providing more meaningful and realistic security arguments. This would allow, for the first time, to ensure that any newly proposed primitive or construction is already resistant to all known attacks, and will considerably increase the confidence on these functions. It will also save a considerable amount of time and allow the field to advance, at last, on solid ground.

Keywords: symmetric cryptography,cryptanalysis,algorithms,attacks,automation,bounds,
Computational investigation of degradation processes in historical paintings using DFT and AI (REPAINT)

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: Türkiye,Belgium
Call: MSCA Postdoctoral Fellowships 2024 (HORIZON-MSCA-2024-PF-01, 2024)
Start date: 2025-10-01
End date: 2027-09-30
Duration (months): 24.0
Total project cost (EUR): 165205.2
EU funding (EUR): 165205.2
Participants: 2
Project status: SIGNED

This project focuses on understanding of pigment degradation in 19th to 20th-century paintings caused by environmental factors such as humidity, temperature, and pollutants. By integrating advanced computational techniques, density functional theory (DFT), ab initio molecular dynamics (AIMD) simulations, and artificial intelligence (AI), the research aims to provide a detailed understanding of how these factors affect the chemical stability and degradation pathways of historical pigments at a molecular level. Static DFT calculations will be used to explore the electronic and optical properties of pigments, while AIMD simulations will examine how environmental conditions affect their degradation by revealing the structural changes. Using these computational results, AI models will be developed to predict how pigments degrade based on their composition and environmental conditions by capturing changes over time that static methods can't fully show. This approach will include a comparative study of pigments from different artworks to enhance the robustness of predictive models. The project aims to advance materials science and conservation by creating a comprehensive database that will offer data-driven guidelines to help extend the life of valuable historical artworks. This interdisciplinary approach aims to benefit both the scientific community and conservation professionals by representing an important step forward in the preservation of cultural heritage for future generations.

Keywords: dft,dft ai,historical paintings,degradation processes