Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : NEON (Horizon Europe, appel 2022, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Computer Science and Informatics
Entité participante : Université de technologie de Delft — Pays : Pays-Bas — Rôle : PI
Acronyme de l'entité : TU Delft
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1996795.0 €

An under-explored problem in Social Signal Processing (SSP) is human social intent detection. SSP develops automated systems to interpret human social behaviour from sensors such as cameras, microphones, and wearables. Prior work estimating intent uses scenarios that are constrained enough so that the intent is determined by a congruent outcome. In reality, this is not true, otherwise emergent leaders are never female because they do not speak up and black minorities are criminals because they are often seen interacting with police. NEON addresses intention detection in more open-ended contexts involving large unstructured social gatherings such as networking or mingling events. During these events, there are no prearranged conversations, multiple conversations can occur at the same time, and all conversation come about via coordination with multiple independent actors with their own possibly conflicting goals. How do we train machines to perceive plausible intentions? Asking the individual to continuously report on their immediate intentions would contaminate their spontaneous social behaviour. NEON hypothesises that plausible social intentions are perceivable by external observers though the explanations of why (based on the behaviours of the individual and the surround social context) may vary depending on the perceivers own life experiences. To this end, NEON will develop a novel framework to harvest and learn from social intentions and their relation to future outcomes using a novel multi-task learning set up that clusters both on the traits of the perceivers as well as the observed individuals, a unified theory that situates conversations in free standing groups in both space and time and a novel Graphical Neural Network architecture to model it through multi-sensor cross modal learned neural representations. Aside from being a significant advance for SSP, NEON also benefits a range of other fields from human-robot interaction to organisational psychology

Mots-clés : social signal processing,human behavior analysis,multimodal interaction,affective computing
Projet ERC : AM-IMATE (Horizon Europe, appel 2022, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Materials Engineering
Entité participante : Université de technologie de Delft — Pays : Pays-Bas — Rôle : PI
Acronyme de l'entité : TU Delft
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1999491.0 €

I envision a world in which the responsive power of biological systems is harnessed through direct integration in materials and structures. Biological materials constantly adapt to their environment, display lower embodied energy, and possess remarkable mechanical properties granted by their hierarchical structures. Adapting these principles to human-made objects promises to disrupt the way we engineer our high-performance critical structures. However, today’s engineering materials remain lifeless, and show only limited abilities to adapt and reinforce under load, or to heal and repair in response to damage. By addressing the lack of knowledge in (i) organism signalling, (ii) additive fabrication and (iii) responsive bio-inspired composites, I will be amongst the first to create living composites that will bridge the gap between biology and stiff, lightweight engineering structures.  To achieve my vision of living structures, I will cross boundaries between three previously disconnected disciplines. I will (i) exploit the intrinsic electrical activity of fungal mycelium networks to couple electrical and mechanical response in mycelium composite materials, (ii) enable complex shaping using new additive manufacturing technologies to create bio-inspired living objects augmented with sensing and vasculature networks, and (iii) develop topology optimised geometries and large-scale living structures that adapt and remodel during use. The project combines these aspects to exploit organism growth and function in a way never done before to realise stiff, tough, and responsive materials, while paving the way for a future of living material structures.

Mots-clés : additive manufacturing,bio inspired composites,living materials and structures
Projet ERC : LOOP (Horizon Europe, appel 2021, Consolidator grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Study of the Human Past
Entité participante : Université de la Ruhr à Bochum — Pays : Allemagne — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1996496.0 €

In the Eastern Mediterranean, the four decades between 1880 and 1920 were a time of imperialism, globalisation and Ottoman state building, but also of profound social differentiation, fuelled by an unprecedented degree of human mobility and migration. Therefore, in this period we find the roots of many social formations that have remained relevant until the present. My focus is on the individual and collective practices for coping with various challenges and on census-taking as a social process. It will open up new perspectives on social and cultural dynamics in late Ottoman Palestine, in a historical context defined by European imperialism, Ottoman state building and globalisation. The main research question is: which social strategies did late Ottoman Palestinians employ, across ethnic, religious and class divides, to confront challenges on the individual and collective levels? These include fostering social advancement of one’s household or coping with economic stress. My hypothesis is that an accumulation of individual actions led to the constant emergence and re-emergence of social formations.  Using the census process and its data I will establish yardsticks that will make it possible to compare social practices across the region and beyond, and thus contribute to ongoing efforts to write a global social and cultural history and it will develop a theoretical framework and methodological standards that will be useful for similar research projects. Specifically, the project aims to set new standards for how to realise the vision of an HGIS for the entire Ottoman Empire. Enabling comparison with other sources it may also offer intriguing new perspectives for the study of colonialism, notably under the British Mandate.

Mots-clés : palestine ottoman empire social history cultural history economic history social differentiation social practices social strategies census census taking as a social process historical gis
Projet ERC : RES-NOVA (Horizon Europe, appel 2022, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Fundamental Constituents of Matter
Entité participante : Istituto nazionale di fisica nucleare — Pays : Italie — Rôle : Partner
Acronyme de l'entité : INFN
Type d'entité : Recherche
Financement ERC de l'entité : 406250.0 €

One of the most energetic events in the Universe is the core-collapse Supernova (SN) where almost all the star's binding energy is released as neutrinos. These particles are direct probes of the processes occurring in the stellar core and provide unique insights into the gravitational collapse and the neutrino properties. Currently, astroparticle physics is in need of SN observations and of a detection technique highly sensitive to all neutrino flavors. RES-NOVA will revolutionize how we detect neutrinos from astrophysical sources by deploying the first array of cryogenic detectors made from archaeological Pb. Neutrino detection in RES-NOVA is facilitated by the newly discovered Coherent Elastic neutrino-Nucleus Scattering (CEvNS). It enables the first measurement of the full SN neutrino signal, eradicating the uncertainties related to flavor oscillations. To fully exploit the advantages of CEvNS, RES-NOVA ennobles Pb from being a passive shielding to the most sensitive detector component. Pb has the highest cross-section, 10^4 times higher than all used detection channels, enabling the deployment of a cm-scale neutrino observatory. The unconventional approach of RES-NOVA is to use ultra-pure archaeological Pb and run it as a cryogenic detector with low-energy threshold (<1 keV) and unprecedented background (<0.001 c/ton/keV/s). These features also open new opportunities in multi-messenger astronomy, Dark Matter, and neutrino property studies. The success of my pioneer work in operating archaeological Pb-based cryogenic detectors is pivotal for RES-NOVA realization. RES-NOVA will survey 90% of the potential galactic SNe, with only a total detector volume of (30 cm)^3. Future detector upgrades will enhance our SN-sensitivity into the uncharted territory >1 Mpc and increase the SN observation rate. RES-NOVA has the potential to lay the foundations for a future generation of European neutrino telescopes, as all its SN neutrino detectors are currently going offline.

Mots-clés : supernova,neutrino,cryogenic detectors
Projet ERC : CityLife (Horizon Europe, appel 2023, Consolidator grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Study of the Human Past
Entité participante : Université Johannes-Gutenberg de Mayence — Pays : Allemagne — Rôle : Partner
Acronyme de l'entité : JGU
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 417500.0 €

CityLife explores, from a bioarchaeological perspective, how historical populations adapted to an urban environment and developed resilience to the disadvantages of urban life. By exploiting the vast amount of information contained in human skeletal remains, the project will clarify the roles of biological factors in the durability and sustainability of pre-industrial urban societies. Newly developed osteological, chemical isotope, and genomic methods will be used in this project, together with cutting-edge tools for statistical evaluation. CityLife will evaluate the living conditions, economy, population structure, pathogen load, and immune defenses in a sample of more than 4,500 skeletons from a hotspot of European urban culture: Thessaloniki. This city in northern Greece still exists today, and in historic times it formed a bridge between the Roman West and the Byzantine East. Thessaloniki offers the unique constellation to study urban life from 300 BC to AD 1,500 and thus to draw inference about an urban population in a single place continuously over 1,800 years. The main objectives of the project are to a) infer urban living standards by studying secular changes in anthropometric indexes, infant diet, childhood stress, and trauma in a combined manner; b) investigate the resilience and sustainability of urban food systems by reconstructing individual diets and local supply networks; d) investigate social structures, religious cohabitation, and migration by genetically reconstructing the degree of kin and non-kin relationships; and e) explore the effects of pathogen exposure on human evolution and health by studying genes associated with increased immunological response and the oral microbiome. CityLife will examine empirically tangible aspects of biocultural development to answer the simple question of how humans became urban species.

Mots-clés : biological anthropology,urban history,human evolution,paleodiet,paleogenetics,biological standards of living,population genetics,epidemiology
Projet ERC : EvolCommunity (Horizon Europe, appel 2023, Consolidator grants)
Domaine scientifique : Life Science
Panel : Environmental B iology, Ecology  and E volution
Entité participante : Université Johannes-Gutenberg de Mayence — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : JGU
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1998383.0 €

In nature, organisms live in communities and form complex trophic interactions. Understanding how multitrophic communities evolve and respond to environmental changes is a fundamental and pressing challenge in face of global change. While research in evolutionary biology revealed that a warming climate can drive adaptive evolution of individual organisms in the community, studies from community ecology showed that a warming climate can alter trophic interactions and community structure, which in turn changes the (co)evolutionary trajectory of interacting species. Thus, integrating evolutionary and ecological responses is crucial to understand the climate responses of individual species and communities. However, methodological challenges have hampered empirical studies until now.  EvolCommunity will address these challenges by experimentally evolving populations of three interacting species (aphid, duckweed, and daphnia) in their native communities using outdoor mesocosms with different climate conditions. We will quantify how warming shapes the function and evolution of the multitrophic community in real-time. By manipulating climate-driven plant evolution, we will determine whether plant evolution alters the community’s response to climate change. We will also assess whether the interacting species coevolve in the community by quantifying the reciprocal selection imposed from their evolutionary changes. We will investigate the molecular mechanisms underlying (co)evolution using state-of-the-art genetic tools.  Using a combination of experimental evolution, community manipulation, and cutting-edge genetic and analytic tools, EvolCommunity will push the research boundaries of evolutionary ecology by revealing the mechanisms and processes of community evolution at work. The outcomes will open new research avenues in evolutionary ecology by establishing a new methodological framework that integrates evolutionary biology and community ecology in natural communities.

Mots-clés : community evolution plant herbivore interactions
Projet ERC : DeciFERR (Horizon Europe, appel 2023, Consolidator grants)
Domaine scientifique : Life Science
Panel : Physiology in Health, Disease and Ageing
Entité participante : Université de Wurtzbourg — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : Julius-Maximilians-Universität Würzburg
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1985356.0 €

Ferroptosis is a cell death modality triggered by the accumulation of oxidised lipids, a process known as lipid oxidation, and associated with a multitude of pathological conditions, including ageing, neurodegeneration, and cancer. On the flip side, recent studies demonstrated that targeting pathways contributing to the prevention or repair of oxidised lipids is a powerful strategy to eradicate therapeutically challenging entities, including neuroblastoma, a pediatric malignancy reported to be remarkably sensitive to ferroptosis. However, therapeutic breakthroughs targeting this pathway are elusive due to our incomplete understanding of the factors controlling this process. DeciFERR will address this critical knowledge gap and identify strategies to trigger ferroptosis. This will be accomplished by discovering and characterising novel mechanisms regulating the stability of key ferroptosis suppressors, thus providing opportunities to develop tailored strategies to target ferroptosis-sensitive entities.  This project rests on our pioneering works identifying two major break systems operating against lipid peroxidation, glutathione peroxidase 4(GPX4) and ferroptosis suppressor protein 1 (FSP1). In Aim 1, using a combination of novel cellular model and target-oriented phenotypic screens, we will characterise and target pathways involved in selenocysteine uptake, mobilisation and recycling, which we found essential for the stability of selenoproteins, including GPX4. In Aim 2, we will dissect metabolic and cellular states that determine the antioxidant capacity of membranes via FSP1-dependent mechanisms using a combination of cellular systems and functional genetic screens. DeciFERR will lead to a comprehensive understanding of how ferroptosis is orchestrated and will expand the druggable inventory, providing innovative strategies that will be put to test and could ultimately pave the way for efficacious therapies against malignancies that still defy current treatments.

Mots-clés : ferroptosis,lipid peroxidation,solute carriers slc
Projet ERC : HomE (Horizon Europe, appel 2021, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Computer Science and Informatics
Entité participante : Université polytechnique de Catalogne — Pays : Espagne — Rôle : PI
Type d'entité : Recherche
Financement ERC de l'entité : 2680195.0 €

Deep learning (DL) is widely used to solve classification problems previously unchallenged, such as face recognition, and presents clear use cases for privacy requirements. Homomorphic encryption (HE) enables operations upon encrypted data, at the expense of vast data size increase. RAM sizes currently limit the use of HE on DL to severely reduced use cases. Recently emerged persistent memory technology (PMEM) offers larger-than-ever RAM spaces, but its performance is far from that of customary DRAM technologies. This project aims at sparking a new class of system architectures for encrypted DL workloads, by eliminating or dramatically reducing data movements across memory/storage hierarchies and network, supported by PMEM technology, overcoming its current severe performance limitations. HomE intends to be a first-time enabler for the encrypted execution of large models that do not fit in DRAM footprints to execute local to accelerators, hundreds of DL models to run simultaneously, and large datasets to be run at high resolution and accuracy. Targeting these ground-breaking goals, HomE enters into unexplored field resulting from the innovative convergence of several disciplines, where wide-ranging research is required in order to assess current and future feasibility. Its main challenge is to develop methodology capable of breaking through the existing software and hardware limitations. HomE proposes a holistic approach yielding highly impactful outcomes that include novel comprehensive performance characterisation, innovative optimisations upon current technology, and pioneering hardware proposals. HomE can spawn a paradigm shift that will revolutionise the convergence of the machine learning and cryptography disciplines, filling a gap of knowledge and opening new horizons such as DL training on HE, currently too demanding even for DRAM. HomE, based on solid evidence, will unveil the great unknown of whether PMEM is a practical enabler for encrypted DL workloads.

Mots-clés : deep learning inference heterogeneous memory systems high performance computing homomorphic encryption persistent memory
Projet ERC : LOTIS (Horizon Europe, appel 2024, Consolidator grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Soci al World and Its Interactions
Entité participante : Université de la Ruhr à Bochum — Pays : Allemagne — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1998018.0 €

The places where people live and spend their time seem to matter for loneliness, but previous research provides mixed evidence for this link. The core argument of LOTIS is that to understand why, when, and for whom places contribute to loneliness, the current perspective on the link between place and loneliness needs to be fundamentally shifted towards a dynamic view. I propose a novel theoretical framework linking a person’s momentary loneliness to how the place is subjectively perceived by this person at a given time, which in turn is influenced by the objective, observable characteristics of this place, characteristics of the person, and individual mobility patterns, i.e., how often, for how long, and in what order places are visited. To test this framework, first, a new dimensional taxonomy that allows describing perceived character-istics of places systematically and comprehensively is developed and applied to the geographically diverse city of Bochum, Germany, using a citizen science approach. Second, the short-term and long-term reciprocal dynamics of place, mobility, and loneliness will be examined in a longitudinal meas-urement burst study where participants track their current location using GPS and report their percep-tions of their current locations and their momentary loneliness four times over a period of three years. Third, the causal processes that link places to loneliness will be tested using laboratory experiments and a natural field experiment. LOTIS has the potential to significantly change how the associations among places, mobility, and lone-liness are conceptualized and studied by (a) moving from a static to a dynamic perspective, (b) incor-porating both objective and perceived characteristics of places, and (c) considering individual mobility patterns. In addition, the insights gained in LOTIS can be used to develop evidence-based interven-tions and public policy measures against loneliness.

Mots-clés : loneliness,socioecological psychology,mobility patterns,mobile sensing,individual differences
Projet ERC : MarDepend (Horizon Europe, appel 2024, Consolidator grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Study of the Human Past
Entité participante : Conseil national de la recherche — Pays : Italie — Rôle : Partner
Acronyme de l'entité : CNR
Type d'entité : Recherche
Financement ERC de l'entité : 400000.0 €

MarDepend seeks to understand the existential dependency of states and communities on maritime trade. It aims to analyse and quantify how trade, geography, and conflict were interrelated in antiquity, with a focus on the city-state of Syracuse in Sicily. The study will explore economic structures, trade balance, and the impact of maritime routes on trade during both peace and war. Syracuse, a key maritime power from the early 5th century BCE until being conquered by Rome in 212 BCE, serves as an ideal case study. Its position at the crossroads of ancient maritime trade, from which it engaged with a wide range of actors, and its largely consistent trade policies over centuries make it particularly relevant and provide a wealth of evidence, in quantity and quality, conducive to quantitative economic analysis. Building on the case of Syracuse, MarDepend establishes maritime dependencies as a framework for comprehending global trade and political dynamics across diverse historical periods. MarDepend, characterised by an innovative interdisciplinary approach and a broad methodological basis, combines historical research, archaeology, marine engineering, oceanography, and economic theory through modelling of wind, waves, and currents, measuring the performance of ancient ships with the help of Computational Fluid Dynamics, reconstructing trade routes through simulations, analysing material evidence (coins, inscriptions, amphorae), and developing a formal economic model for ancient trade. Advanced software and digital tools analyse the data and synthesise it in an open-access GIS. The unique approach provides a foundation for applying analogous methodologies to investigate the trade dependencies in a much broader historical and geographical context, such as a diachronic investigation of the relationship between trade and conflict. The research holds the potential to reshape our understanding of ancient economies and maritime history.