Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : MICROECO (Horizon Europe, appel 2021, Starting grants)
Domaine scientifique : Life Science
Panel : Integrative B iology : from Genes and Genomes to S ystems
Entité participante : Université d'Helsinki — Pays : Finlande — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1485413.0 €

The gut microbiota has wide-ranging effects on host health and represents a promising target for therapeutic manipulation, particularly in early life. Imbalances in the gut microbiota precede the dThe gut microbiota has wide-ranging effects on host health and represents a promising target for therapeutic manipulation, particularly in early life. Imbalances in the gut microbiota precede the development of conditions such as overweight and immunological diseases, which exert a significant burden on society and on individuals. Early identification and treatment of gut microbiota imbalance in childhood thus offers great potential in combatting these problems, and will become an important part of health care in the future. However, achieving this goal will require a high-level understanding of the processes that regulate the microbial populations. Currently our knowledge of the principles governing gut microbiota responses to treatments is insufficient for reliable and targeted microbiota modification. I hypothesize that conceptual limitations are a significant reason for the current inability to reliably predict microbiota responses to treatments and to modify the microbiota. In this interdisciplinary project, based on daily multiomic time series of child gut microbiota and diet and health diaries, I integrate the theoretical and analytical framework of population ecology, novel next-generation metagenomics-based high-resolution quantitative microbiota profiling, and genome-scale metabolic reconstructions into an ecosystem model of the child gut microbiota. The result will be an unprecedented level of understanding of how the gut microbes interact and respond to external forces. The concept can be applied widely to study the numeric and functional microbiota responses to any treatment and to design targeted interventions based on the predicted responses. The project represents the important next step in microbiota research from description to mechanistic understanding.

Mots-clés : human gut microbiota,metagenomics,biotic interactions,ecosystem ecology
Projet ERC : SCARLET (Horizon Europe, appel 2025, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Studies of Cultures and Arts
Entité participante : Université nouvelle de Lisbonne — Pays : Portugal — Rôle : PI
Acronyme de l'entité : UNL
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1499697.0 €

The textile industry faces significant environmental challenges. In response to the increasing demand for sustainable practices and the European Union’s Sustainable Development Goals, SCARLET project aims to revolutionise the textile community by optimising historical recipes for eco-friendly applications. By investigating historical dyeing techniques, SCARLET aims to bridge the gap between traditional practices and modern sustainability standards. This research will validate the eco-friendliness of these recipes and provide practical solutions for SMEs, designers, artists, and the wider textile community seeking alternatives. This will be addressed in the following key points: 1) Heritage and Innovation: SCARLET will combine traditional knowledge with contemporary research to create sustainable dyeing practices. 2) Community Empowerment: The project empowers the textile community to incorporate natural dyes into their work by developing accessible resources. 3) Environmental Impact Reduction: SCARLET will address the oversight of colourants in current sustainability guidelines, offering solutions that significantly reduce the ecological footprint of textile production. SCARLET will undertake a comprehensive approach that begins with an in-depth study of historical dyeing recipes from the 15th to the 18th century across Iberia, Italy, England, and France. The project will focus on interpreting, reconstructing and analysing historical recipes and assessing their suitability for contemporary use. Finally, recognising the gap between historical knowledge and contemporary practice, SCARLET will establish a creative hub, which will provide accessible resources and workshops, empowering the textile community to harness the full potential of natural dyes. By combining historical insights with cutting-edge research, SCARLET addresses the sustainable transformation of textile production while fostering a deeper appreciation for cultural heritage.

Mots-clés : wool natural dyes sustainable design eco friendly formulations
Projet ERC : FINNPEDHEART (Horizon Europe, appel 2022, Starting grants)
Domaine scientifique : Life Science
Panel : Prevention,  Diagnosis and T reatment of Human Diseases
Entité participante : Université d'Helsinki — Pays : Finlande — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1495845.0 €

One in a hundred infants is born with a congenital heart defect (CHD). Both genetic and environmental risk factors, such as maternal diabetes and obesity, are known to cause CHD, however, little is known about the disease mechanisms behind these risks. CHD can occur as an element of a syndrome, in conjunction with other anomalies, or as an isolated defect. I propose that there is an etiologically distinct “environmental CHD” subgroup, where in addition to the child’s genes, maternal genetics and gene expression play a major role in disease development. Moreover, I propose that in these cases the genetic risk profile predisposes the woman for both having offspring with CHD and having early onset atherosclerotic disease. My objective is to study how maternal genetics and maternal cardiovascular morbidity as an environmental risk contribute to the risk for having offspring with CHD. In addition, the multifactorial aetiology in terms of the presence of both risk factors, will be studied using a unique dataset available only in Finland. Three different substudies will be conducted: 1) Finnish national registers gathering health related information of all Finns from birth to death will be used to determine the presence of atherosclerosis and related traits, such as hypertension and coronary artery disease, in mothers who have offspring with CHD compared to those without (tot. N = 1 million). 2) Maternal genetic risk loci for having CHD in the offspring will be sought in the FinnGen study (tot. N = 0.5 million). 3) Maternal 1st trimester serum samples from pregnancies with and without CHD will be analysed to identify CHD associated biomarkers (tot. N = 3200).  The study results will provide important information on how the combination of maternal genetic and environmental risk factors contribute to cardiac developmental defects during early pregnancy and offer new insights for future research on the cellular and molecular mechanisms of cardiac development.

Mots-clés : pediatric cardiology,congenital heart disease,genetics,biomarkers,obstetrics
Projet ERC : ILLUMINATOR (Horizon Europe, appel 2023, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Universe Sciences
Entité participante : Université d'Helsinki — Pays : Finlande — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2211196.0 €

This research program will use first-principles radiative plasma simulations to understand how neutron stars radiate. Neutron stars are the culprits of the most infamous astrophysical emission enigmas: 1) pulsar radio emission, 2) multi-messenger signals of compact-object binary mergers, and 3) simultaneous generation of giant flares and fast radio bursts from magnetars. These emission mechanisms have remained elusive because we do not have a self-consistent theory that combines plasma physics (describing microscopic motions and energy dissipation of the magnetized gas) and radiative processes (describing the reprocessing of the energy into radiation).  This project combines the forefront plasma physics theory with exascale high-performance computing technologies to achieve two breakthroughs: 1) generation of first-principles 3D models of the radiative plasmas around pulsars, mergers, and magnetars; and 2) development of a novel open-source simulation toolkit for self-consistent and high-fidelity modeling of astroplasmas. These enable a quantitative understanding of the unsolved emission mechanisms (including efficiency, variability, and output spectra) and direct comparison to observations.  Analyzing astronomical observations with these superior physics-constrained models enable direct tests of their validity and a leap in improving the accuracy of the modern nuclear/particle physics theories of the still-unknown neutron star equation of state. The PI has a world-leading role in computational astroplasma physics, an established record of impactful and innovative research in the astrophysics of neutron stars, and 10 years of experience in state-of-the-art high-performance computing solutions.

Mots-clés : neutron stars,magnetars,pulsars,mergers,fast radio bursts,radiative processes,fluid dynamics,quantum electrodynamics,high performance computing,particle in cell method,magnetohydrodynamics,magnetic reconnection,turbulence,magnetically dominated plasmas
Projet ERC : ALcHyMiA (Horizon Europe, appel 2023, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Mathematics
Entité participante : Université de Vérone — Pays : Italie — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1500000.0 €

ALcHyMiA will make substantial progress in applied mathematics, targeting long-time stable and self-consistent simulations in general relativity and high energy density problems, via the development of new and effective structure preserving numerical methods with provable mathematical properties. We will devise innovative schemes for hyperbolic partial differential equations (PDE) which at the discrete level exactly preserve all the invariants of the continuous problem, such as equilibria, involutions and asymptotic limits. Next to fluids and magnetohydrodynamics, key for benchmarks and valuable applications on Earth, we target a new class of first order hyperbolic systems that unifies fluid and solid mechanics and gravity theory. This allows to study gravitational waves, binary neutron stars and accretion disks around black holes that require the coupled evolution of matter and spacetime. Here, high resolution and minimal dissipation at shocks and moving interfaces are crucial and will be achieved by groundbreaking direct Arbitrary-Lagrangian-Eulerian (ALE) methods on moving Voronoi meshes with changing topology. These are necessary to maintain optimal grid quality even when following rotating compact objects, complex shear flows or metric torsion. They also ensure rotational invariance, entropy stability and Galilean invariance in the Newtonian limit. The breakthrough of our new Finite Volume and Discontinuous Galerkin ALE schemes lies in the geometrical understanding and high order PDE integration over 4D spacetime manifolds. The high-risk high-gain challenge is the design of smart DG schemes with virtual, bound-preserving, genuinely nonlinear data-dependent function spaces, taking advantage of the Voronoi properties. Finally, it is an explicit mission of ALcHyMiA to grow a solid scientific community, sharing know-how by tailored dissemination activities from top-level schools to carefully organized international events revolving around personalized interactions.

Mots-clés : first order hyperbolic partial differential equations pde with involutions,high order methods on manifolds,arbitrary lagrangian eulerian ale methods on moving voronoi meshes with topology changes,finite volume fv and discontinuous galerkin dg schemes,virtual finite element methods vem,structure preserving sp schemes,well balanced wb methods,bound preserving schemes,mesh optimization,polytopes,einstein field equations,unified model of continuum mechanics,teleparallel gravity theory,numerical general relativity,computational astrophysics,binary neutron stars,gravitational waves
Projet ERC : CONVEY (Horizon Europe, appel 2022, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Computer Science and Informatics
Entité participante : Technion - Institut de technologie d'Israël — Pays : Israël — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1470250.0 €

From self-driving cars to agents recommending medical treatment, Artificial Intelligence (AI) agents are becoming increasingly prevalent. These agents have the potential to benefit society in areas such as transportation, healthcare and education. Importantly, they do not operate in a vacuum—people interact with agents in a wide range of settings. To effectively interact with agents, people need to be able to anticipate and understand their behavior. For example, a driver of an autonomous vehicle will need to anticipate situations in which the carfails and hands over control, while a clinician will need to understand the treatment regime recommended by an agent to determine whether it aligns with the patient’s preferences.  Explainable AI methods aim to support users by making the behavior of AI systems more transparent. However, the state-of-the-art in explainable AI is lacking in several key aspects. First, the majority of existing methods focus on providing “local” explanations to one-shot decisions of machine learning models. They are not adequate for conveying the behavior of agents that act over an extended time duration in large state spaces. Second, most existing methods do not consider the context in which explanations are deployed, including to the specific needs and characteristics of users. Finally, most methods are not interactive, limiting users’ ability to gain a thorough understanding of the agents.  The overarching objective of this proposal is to develop adaptive and interactive methods for conveying the behavior of agents and multi-agent teams operating in sequential decision-making settings. To tackle this challenge, the proposed research will draw on insights and methodologies from AI and human-computer interaction. It will develop algorithms that determine what information about agents’ behavior to share with users, tailored to users’ needs and characteristics, and interfaces that allow users to proactively explore agents’ capabilities.

Mots-clés : explainable artificial intelligence,human ai interaction
Projet ERC : DIM-FRACTAL (Horizon Europe, appel 2025, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Mathematics
Entité participante : Technion - Institut de technologie d'Israël — Pays : Israël — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1500000.0 €

We consider the dimension of stationary fractal measures. Our examples include self-affine, self-similar, and Furstenberg measures, which are among the most fundamental and studied fractal objects. The dimension of such a measure has a natural upper bound defined in terms of entropy, Lyapunov exponents, and the dimension of the ambient space. Equality to the upper bound is expected in the absence of obvious algebraic obstructions. In very simple situations, this equality is easy to demonstrate and was known to hold long ago. In more complicated cases, it has been shown to hold almost surely under a natural randomization of the parameters.  On the other hand, proving the expected equality under the minimal conjectured assumptions, or even under some mild algebraic conditions, is an extremely challenging problem. In recent years, there has been considerable progress in this direction. However, due to major obstacles in current methods, a satisfactory solution is still a long way off. These obstacles mainly stem from high dimensionality of the ambient space, and from lack of separation in the associated semigroup.  The primary goal of the proposed research is to make substantial progress in verifying the equality by addressing the aforementioned obstacles through the use of new techniques and ideas. Our suggested arguments include methods from additive combinatorics, ergodic theory, and the theory of random products of matrices.  To address difficulties caused by lack of separation, we suggest extending the theory developed for Bernoulli convolutions, and its partial generalization to the setup of three maps, to systems consisting of more maps. To tackle high dimensionality difficulties, we propose an approach requiring the factorization of the Furstenberg boundary maps. By implementing these strategies, we expect our research to play a crucial role in forming a more unified and complete dimension theory of stationary fractal measures.

Mots-clés : dimension of measures,lyapunov dimension,self similar measure,self affine measure,furstenberg measure
Projet ERC : EPIC (Horizon Europe, appel 2024, Starting grants)
Domaine scientifique : Life Science
Panel : Physiology in Health, Disease and Ageing
Entité participante : Technion - Institut de technologie d'Israël — Pays : Israël — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1500000.0 €

Immune cells monitor and eliminate cancer cells, and thus keep tumors in check along the lifespan of an organism. However, tumors have evolved various mechanisms to avoid immune surveillance. Therefore, understanding these mechanisms and interfering with them to facilitate immune cell eradication of tumor cells is the focus of many successful immunotherapies. However, the efficacy of immunotherapy is limited to only a small fraction of patients and only certain types of cancers. Therefore, it is crucial to understand the immune-tumor interactions to develop new treatments. Moreover, tumor evasion mechanisms interfere with such treatments, as compensatory programs ensue soon after therapeutic intervention. These compensatory programs are not limited to tumor cells, but also occur in the stromal compartment of the tumor microenvironment (TME), which provides indispensable support to the tumor, and is often overlooked as potential target for intervention. Here we aim to gain a fundamental understanding of all cellular networks within the TME, to elucidate the roles and programs carried out by each cellular element participating in the complex, multilevel interactions that occur before therapeutic intervention and afterward. Toward this goal, we will map the entire spectrum of immune and stromal cell interactions in the TME. We will identify negative- and positive-tumor-regulator dependent programs, primary and compensatory, unique and shared-across pathogenic conditions, and cell-intrinsic and extrinsic programs (Aim 1). Additionally, we aim to identify conserved mouse and human pathways using a parallel mouse and human tumor slice culture system (Aim 2). Based on Aims 1 and 2, we will test and validate new candidates for targeted rational combination therapy in-vivo (Aim 3). Our findings will lay the foundations for a fundamental understanding of tumor immunity dynamics in the TME and create a paradigm shift in immunotherapy

Mots-clés : tumor immunology,immunotherapy,cellular networks,stroma,tumor microenvironment
Projet ERC : NANODYNAMICS (Horizon Europe, appel 2023, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Physical and Analytical Chemical Sciences
Entité participante : Technion - Institut de technologie d'Israël — Pays : Israël — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1812500.0 €

Metal nanoparticle-based catalysts drive our chemical industry and will be an essential tool to shift away from fossil-resources. Despite their exigence, new catalysts are often still found by trial and error rather than designed rationally. Although recent fundamental studies from our own research and others yield important new insights, there is a lack of methodology to investigate the subtle transient details missing in our understanding at the very high pressures that are often industrially relevant. Details such as reaction mechanisms, or dynamic surface equilibria at more than 100 bar are evidently greatly relevant to rationally designing better catalysts, yet have so far been outside of the realm of experimental characterization which hampers progress. Our key objective is to generate fundamental understanding of supported metal nanoparticle catalyst dynamics at work under relevant high-pressure conditions (up to 100 bar), with a strong focus on studying the Haber-Bosch reaction. To achieve this, we will utilize three recent developments: We will (1) employ specially designed reactors where laminar flow standing wave stimulation will be used, (2) perform high-time resolution resonant-Surface-enhanced infrared spectromicroscopy, and spatially resolved quick-X-ray absorption spectroscopy and (3) use our noise classification algorithm and further statistical data mining for quantification of surface site participation, and dynamics. In this way we will be able to differentiate important but miniscule reaction details from noise. These novel methods will be combined to gain insight into dynamic active sites, and equilibria that may exist at high pressure. The new insights will shift our fundamental knowledge from ‘static approximation’ to ‘dynamic reality’ and will offer direction in a new path of activity design improvements, dynamic site tailoring.

Mots-clés : operando spectroscopy,high pressure experimentation
Projet ERC : THEORYCRAFT (Horizon Europe, appel 2021, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Computer Science and Informatics
Entité participante : IT University of Copenhagen — Pays : Danemark — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1471056.0 €

How can theory inform design practice? This question is among the grand challenges in both Human-Computer Interaction (HCI) and games research. Despite numerous efforts to bridge the research-practice gap, the two poles seem irreconcilable. Instead of a robust and generalizable knowledge base to tackle foundational problems around technology use, cumulative knowledge building is impeded by weak empirical studies and rampant theoretical misconceptions. Instead of providing practitioners with useful theory-based insights, research results often remain too abstract and not sufficiently actionable to be adopted into design practice.  THEORYCRAFT tackles this conundrum by means of theory translation, demonstrating how theory needs to be transformed and specified to bridge research and design practice. Building on the PI's excellent track record in theory-building games research, we approach theory translation from four angles: 1) We investigate how game design practitioners make use of theory to identify avenues for productive theory translation. 2) We translate theoretical propositions from psychology to build explanatory theories of ill-understood games phenomena. 3) We develop translational resources that convey theoretical propositions in a manner that is useful and actionable for game design. 4) We evaluate the translated theories in terms of their utility to bridge research and design practice. Individually, each angle will result in important advances in HCI and games research. Collectively, THEORYCRAFT will produce a breakthrough in transparent and systematic theory translation, which will radically transform how knowledge is built, represented and disseminated – steering HCI and games research towards greater scientific integrity, practical relevance, and impact.

Mots-clés : games,human computer interaction,theory translation,game design,research practice gap