Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : SPARSE-ML (Horizon Europe, appel 2023, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Computer Science and Informatics
Entité participante : Helmholtz Center for Information Security — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : CISPA
Type d'entité : Recherche
Financement ERC de l'entité : 1499285.0 €

Deep learning continues to achieve impressive breakthroughs across disciplines and is a major driving force behind a multitude of industry innovations. Most of its successes are achieved by increasingly large neural networks that are trained on massive data sets. Their development inflicts costs that are only affordable by a few labs and prevent global participation in the creation of related technologies. The huge model sizes also pose computational challenges for algorithms that aim to address issues with features that are critical in real-world applications like fairness, adversarial robustness, and interpretability. The high demand of neural networks for vast amounts of data further limits their utility for solving highly relevant tasks in biomedicine, economics, or natural sciences. To democratize deep learning and to broaden its applicability, we have to find ways to learn small-scale models. With this end in view, we will promote sparsity at multiple stages of the machine learning pipeline and identify models that are scaleable, resource- and data-efficient, robust to noise, and provide insights into problems. To achieve this, we need to overcome two challenges: the identification of trainable sparse network structures and the de novo optimization of small-scale models. The solutions that we propose combine ideas from statistical physics, complex network science, and machine learning. Our fundamental innovations rely on the insight that neural networks are a member of a cascade model class that we made analytically tractable on random graphs. Advancing our derivations will enable us to develop novel parameter initialization, regularization, and reparameterization methods that will compensate for the missing implicit benefits of overparameterization for learning. The significant reduction in model size achieved by our methods will help unlock the full potential of deep learning to serve society as a whole.

Mots-clés : deep learning,sparsity,theory,lottery tickets,cascade processes,complex networks,random graphs
Projet ERC : LACONIC (Horizon Europe, appel 2021, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Computer Science and Informatics
Entité participante : Helmholtz Center for Information Security — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : CISPA
Type d'entité : Recherche
Financement ERC de l'entité : 1482690.0 €

Communication efficiency is one of the central challenges for cryptography. Modern distributed computing techniques work on large quantities of data, and critically depend on keeping the amount of information exchanged between parties as low as possible. However, classical cryptographic protocols for secure distributed computation cause a prohibitive blow-up of communication in this setting. Laconic cryptography is an emerging paradigm in cryptography aiming to realize protocols for complex tasks with a minimal amount of interaction and a sub-linear overall communication complexity. If we manage to construct truly efficient laconic protocols, we could add a cryptographic layer of protection to modern data-driven techniques in computing. My initial results in laconic cryptography did not just demonstrate the potential of this paradigm, but proved to be a game-changer in solving several long standing open problems in cryptography, e.g. enabling me to construct identity-based encryption from weak assumptions. However, the field faces two major challenges: (a) Current constructions employ techniques that are inherently inefficient. (b) The most advanced notions in laconic cryptography are only known from very specific combinations of assumptions, and are therefore just one cryptanalytic breakthrough away from becoming void. This project will make a leap forward in both challenges. I will systematically address these challenges in a work program which pursues the following objectives: (i) Develop new tools and mechanisms to realize crucial cryptographic primitives in a compact way. (ii) Design efficient protocols for advanced laconic functionalities which sidestep the need for inherently inefficient low-level techniques and widen the foundation of underlying assumptions. (iii) Strengthen the conceptual bridge between laconic cryptography and cryptographically secure obfuscation, transferring new techniques and ideas between these domains.
Projet ERC : GAMEchange (Horizon Europe, appel 2024, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Earth System Science
Entité participante : Université de Versailles Saint-Quentin-en-Yvelines — Pays : France — Rôle : PI
Acronyme de l'entité : UVSQ
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1499775.0 €

The representation of soil carbon in models used by the Intergovernmental Panel on Climate Change (IPCC) remains significantly underdeveloped, leading to uncertainty concerning some models predicting soils as carbon sinks and others as sources of carbon dioxide. The development of microbe-explicit models is a very promising avenue for avoiding such inconsistencies and obtaining more accurate soil organic carbon (SOC) predictions. However, these models still suffer from uncertain parameterization due to the lack of data and the high variability in microbial responses at the ecosystem scale. These issues are especially true in carbon-rich northern high-latitude soils that are most vulnerable to large SOC loss with global change. The variability in microbial response at the ecosystem scale is rooted in intricate microscale eco-evolutionary adaptive processes, namely evolution, dispersal, and filtering of community diversity. The diversity in microbiomes, resulting from past selection, influences present adaptive capacity and is referred to as the contingency effect. The GAMEchange project will harness a recent surge of novel microbial genomic data in order to parameterize a new generation of biogeochemical model that accounts for the effect of microbial adaptation on SOC, including contingency effects. GAMEchange will couple the genome-parameterized microscale microbial model with a vegetation land model using a novel emulation approach. This novel coupled model will allow us to compare the 2100 SOC predictions with and without microbial adaptation. This project will produce the first coupled soil microbe-land model parameterized with genomic data, laying the foundation for more realistic microbial models for IPCC climate projections.

Mots-clés : global carbon cycling,soil microbes,ecology and evolution,land models
Projet ERC : UltraDeepMood (Horizon Europe, appel 2025, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Human Mind and Its Compl exity
Entité participante : Université Vie-Santé Saint-Raphaël — Pays : Italie — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1477500.0 €

Our expectations about the world shape our mood and well-being. In extreme contexts, mood can become pathologically depressed as in mood disorders or dementia. Recent studies have begun to suggest a mechanism for how expectations (and their violation) impact human moods. Unfortunately, this mechanism relies on correlational studies since we currently lack tools able to directly manipulate these circuits in healthy humans. UltraDeepMood will combine cutting-edge ultrasound stimulation with imaging and computational modeling to determine the hypothesis that human moods can be changed by modulating expectation signalling in deep brain subcallosal cingulate circuits.  UltraDeepMood will overcome the current major limitations hindering our understanding of mood circuits in humans. First, the lack of non-invasive tools to modulate activity deep in the healthy brain: by using focused transcranial ultrasound stimulation (TUS), a technique I have pioneered in deep primate areas, I will non-invasively manipulate human circuits to causally establish their role in mood. Second, by using TUS to modulate dopamine-projecting areas, I will directly modulate learning and decision processes in the striatum and disentangle them from those underlying mood and well-being in subcallosal anterior cingulate cortex.  UltraDeepMood has three key aims: (1) dissociate the contribution of gray versus white matter TUS to mood connectivity; (2) combine TUS with fMRI and computational models to determine the role of deep cingulate circuits to mood; (3) directly manipulate related circuits of learning and decision-making.  UltraDeepMood will reveal a novel mechanistic insight into the circuits of moods and well-being in the healthy brain. This non-invasive approach will open an unprecedented avenue in shaping our understanding of deep brain circuits. Determining this is foundational for establishing the basis of mood symptoms and developing new therapies.

Mots-clés : human,transcranial ultrasound stimulation,neuromodulation,fmri,computational modelling,mood,subgenual cortex,prediction errors,limbic system,prefrontal cortex,decision making
Projet ERC : PLASTECITY (Horizon Europe, appel 2023, Starting grants)
Domaine scientifique : Life Science
Panel : Physiology in Health, Disease and Ageing
Entité participante : Institut national de la santé et de la recherche médicale — Pays : France — Rôle : PI
Acronyme de l'entité : Inserm
Type d'entité : Recherche
Financement ERC de l'entité : 1499000.0 €

Acute myeloid leukemias (AML) are aggressive blood cancers with poor overall prognosis. The main intervention line is high-dose chemotherapy, often associated with resistance, relapse and long-term side effects. Although predominantly considered as genetic diseases of the hematopoietic system, AML also affect the bone marrow (BM) microenvironment, which contributes to disease pathogenesis. Particularly, we have revealed a thorough remodeling of the vascular tree, with endothelial cells (ECs) displaying dismantled junctions and an embryonic-like molecular signature. Our research hypothesis is that this embryonic-like ECs (E-ECs)– displaying a high grade of plasticity – are progressively enriched during AML progression and foster a leukemia-reinforcing environment. Thus, this proposal aims at (1) deciphering the nature of enriched E-ECs in AML pathogenesis and (2) identifying effective strategies to target them to improve therapeutic response. To this end, we will combine in vivo lineage tracing and OMIC studies in consolidated transplantable models of AML and patient-derived samples to decipher the molecular and clonal dynamics of BM ECs as well as their phenotypic plasticity toward regained Endothelial-to-Hematopoietic and Endothelial-to-Mesenchymal transition potential. We will next explore novel therapeutic avenues by targeting microenvironmental plasticity in AML via candidate genes associated with the aforementioned phenotypes in vivo with engineered CRISPR-nanobodies. Finally, this knowledge will be translated to the human system via pre-clinical validation of putative targets in a state-of-the-art human vascularized BM-on-chip platform. In conclusion, this research proposal will uncover essential molecular mechanisms regulating stem cell niche dynamics in normal and pathological conditions, provide a thorough understanding of the molecular and cellular plasticity of BM ECs and will result in innovative strategies to ameliorate AML clinical treatments.

Mots-clés : vascular system tumor microenvironment genetic engineering stem cells
Projet ERC : Glyco13Cell (Horizon Europe, appel 2023, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Synthetic Chemistry and Materials
Entité participante : Center for Cooperative Research in Biosciences — Pays : Espagne — Rôle : PI
Type d'entité : Recherche
Financement ERC de l'entité : 1500000.0 €

Every human cell is covered by a dense coat of glycans (sugars, carbohydrates). Sugars are the first molecules that viruses encounter when they approach host cells. Many viruses encode lectins to adhere to the outer glycan layer and start infection. In this scenario, Glycoscience holds a tremendous potential for combating infections. Elucidating the molecular basis of infection is essential, but far from trivial. The complexity of the chemistry of glycans, including synthesis, structure, conformation, and dynamics hampers the full knowledge of sugar-mediated recognition events and the development of glycan-based drugs. Surfing the current information on glycan/lectin interactions, we stumble in contradictory outcomes, pointing out the tremendous difficulty of translating in vitro results to the in vivo environment, which limits the translation from the bench to clinics.  I propose an unprecedented strategy to untangle the key glycan’s molecular interaction features breaking the limits in answering fundamental questions related to sugar structure, presentation, dynamics, and eventually function. I will chemically remodel the glycans, directly on the cell surface, using NMR active probes to decode their roles at atomic resolution, while preserving their presentation in a near-to-in-vivo environment. I am in a favoured position to accomplish this project due to my experience in NMR, synthesis, and mammalian cells manipulation. I will combine chemical biology tools, novel chemical and enzymatic synthesis, and NMR-based methods: From chemistry to biology and beyond.  Glyco13Cell will gap down the observed differences between in vitro and in vivo results paving the way for develop novel glycan-based tools for predicting, diagnosing and treating infectious diseases. Now it’s time. The increasing understanding of infection biology with the atomic precision of modern chemical tools will make glycomics run in parallel with genomics & proteoms towards personalized medicine.

Mots-clés : chemo enzymatic synthesis,cell engineering,nmr probes,molecular interactions
Projet ERC : ECCC (Horizon Europe, appel 2022, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Computer Science and Informatics
Entité participante : Université de Haïfa — Pays : Israël — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1489375.0 €

Error-correcting codes are a method for a redundant representation of data, that enables one to can recover the original data even in the presence of some noise or corruption. In addition to their wide practical applicability, error-correcting codes are also supported by a rich theory, with connections to diverse disciplines in mathematics, science, and engineering. A particularly fruitful such connection has been the interplay with the theory of computation, where on the one hand, computational methods were used for the design of error-correcting codes admitting efficient error-correction algorithms, and in the reverse direction, such codes were useful for a variety of applications within the theory of computation.  The current project aims to significantly enhance the aforementioned connections. Our first main objective is to design error-correcting codes that on the one hand, achieve the best possible information-theoretic trade-off between their redundancy and error-resilience, and on the other hand, admit super-fast error-correction algorithms. We further believe that such codes are a powerful tool that can be used for boosting the efficiency of various fundamental computational tasks, and our second main objective is to explore such potential applications. We outline a couple of such potential applications within the theory of computation, to obtaining highly-efficient proof systems, fine-grained inapproximability results, fast derandomization, and code-based cryptography with low overhead.  The goals we plan to pursue are fundamental and long-standing, and even a partial progress on them would be groundbreaking, with theoretical, and potentially also practical, impact. Despite the significant challenge, there has recently been an exciting progress towards these goals (including by the PI), and we consequently believe that we are now in a unique position for pursuing these goals.

Mots-clés : error correcting codes,coding theory,theory of computation,complexity theory
Projet ERC : MARIONETTE (Horizon Europe, appel 2025, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Physical and Analytical Chemical Sciences
Entité participante : Institute of Photonic Sciences — Pays : Espagne — Rôle : PI
Acronyme de l'entité : ICFO
Type d'entité : Recherche
Financement ERC de l'entité : 2174716.0 €

Sunlight is a source of life for plants but also of photodamage. To harvest solar energy “safely”, plants have developed a nanoscale mechanism controlled by small proteins which bind pigments, called light-harvesting complexes (LHCs). At low light intensities, the LHCs harvest and transport solar energy to the sites of photochemistry. Under intense light, LHCs switch function to dissipate excess energy as heat. Through this photoprotective switch, the LHCs efficiently protect plants from photodamage. Yet, how do plants activate the LHC photoprotective switch? Current models assume that the switch is driven by protein conformational changes of the LHCs, regulated by the environment through pH changes and interactions with protein and cofactors. However, no experimental tool implemented in the field of photosynthesis allows to identify the conformational changes responsible of photoprotection and to determine how the environment controls them – limiting our mechanistic understanding of light-harvesting regulation in plants. I will tackle this challenge by: 1) Pioneering the study of LHC nanomechanics via single-molecule optical tweezers, resolved in force and fluorescence, to track LHC conformational changes at single-residue level and identify those driving the photoprotective switch. 2) Leveraging a novel ultrafast multipulse spectroscopic tool — just developed by my group — to rapidly control environmental changes and determine the intermediate steps in the photoprotective switch of the LHCs. 3) Integrating ad hoc molecular dynamics simulations to map how external physiological factors tune the conformational landscape of the LHCs. By implementing a novel optical and computational toolkit, I will advance our understanding of how plants regulate light harvesting at the nanoscale, while establishing a new framework in photosynthesis and photobiology to determine how structure and environment control the function of photosensory proteins across all life domains.

Mots-clés : plant photoprotection light harvesting complex quenching ultrafast spectroscopy molecular dynamics single molecule optical tweezers
Projet ERC : TheMA (Horizon Europe, appel 2023, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Materials Engineering
Entité participante : National Centre of Scientific Research "Demokritos" — Pays : Grèce — Rôle : PI
Acronyme de l'entité : NCSR-D
Type d'entité : Recherche
Financement ERC de l'entité : 1288750.0 €

Two-dimensional (2D) van der Waals layered materials have been acclaimed for their great potential in several fields of condensed matter physics. As applications are starting to appear, increased effort is dedicated to understand their unique electronic, optical, mechanical and chemical properties. However, thermal and thermoelectric (TE) properties of 2D materials remain largely underexplored despite their profound potential impact on one of the most important current scientific and technological challenges: energy management. TheMA is an ambitious project, which aims to create a breakthrough in our understanding and ability to control phonon and energy transport at the nanoscale. Its main goal is to create novel 2D semiconductor nanomaterials and heterostructures for thermal management applications and TE devices for power generation beyond current state-of-the-art. Specifically, by using phonon engineering approaches supported by advanced characterization, the project targets the fabrication and on-chip integration of (a) novel engineered transition metal dichalcogenide (TMD) based nanostructures for heat guiding and superior thermal insulation and (b) TE power generators capable of recycling the waste heat from hot spots or environmental interlinks, to deliver sufficient power to sustain low-power electronics. Ultimate goal of the project is to provide innovative solutions for on-chip energy management and energy harvesting for Information and Communication Technologies, the Internet of Things and 2D nanoelectronic devices.  The research proposed here will go beyond state-of-the-art providing the in-depth understanding of nanoscale energy dissipation and phonon transport in 2D nanomaterials and lay the foundations for the development of future three-dimensional heterogeneous electronics. The findings will drastically enhance the prospects of TMD materials for thermal management and TE applications and boost their integration in the main semiconductor industry.

Mots-clés : 2d materials,phonons,energy transport,thermal management,thermoelectric power generation,phonon engineering
Projet ERC : DECODE-PMD (Horizon Europe, appel 2025, Starting grants)
Domaine scientifique : Life Science
Panel : Molecules of Life: B iological  Mechanisms , Structures  and Functions
Entité participante : Centro de Regulación Genómica — Pays : Espagne — Rôle : PI
Acronyme de l'entité : CRG
Type d'entité : Recherche
Financement ERC de l'entité : 1703070.0 €

Cells tightly regulate mRNA stability to ensure accurate gene expression across diverse cellular states and conditions. Traditionally, selective mRNA degradation has been attributed to the recognition of nucleotide sequence elements by proteins or small RNAs that subsequently recruit decay factors. Conversely, an emerging mechanism termed “peptide-mediated mRNA decay” (PMD) involves the encoded protein: my postdoctoral work revealed how the nascent polypeptide—physically linked to the mRNA during translation by the ribosome—can direct mRNA decay. This process is exemplified by tubulin mRNAs, which are selectively degraded when cells sense excess free tubulin levels. In this novel type of regulation, a recognition factor binds the nascent polypeptide to recruit downstream factors that trigger mRNA degradation. Impaired tubulin PMD results in severe phenotypes like defects in cell division and neurodevelopment. Beyond tubulins, emerging evidence points to critical PMD mechanisms targeting transcripts encoding aggregation-prone proteins. I postulate that PMD represents an entirely unexplored paradigm of gene regulation that dynamically adjusts protein production to ensure cellular fitness. However, the mechanistic understanding of PMD is still limited and the full range of substrates remains unknown. In DECODE-PMD I will unravel how nascent polypeptides direct mRNA degradation on ribosomes and chart the transcriptome-wide map of PMD substrates. Specifically, I aim to (1) decode how mRNA translation and degradation are coupled during tubulin PMD using a biochemical reconstitution approach; (2) decipher the physiological triggers of tubulin PMD and its regulation; and (3) harness advanced sequencing methods to systematically identify PMD substrates and derive common mechanistic principles. Our innovative work will provide a conceptual framework for how cells exploit nascent polypeptide recognition for selective tuning of mRNA stability to maintain protein homeostasis.

Mots-clés : rna degradation protein synthesis ribosome gene regulation transcriptomics structural biology microtubules cytoskeleton cell cycle