Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : UnStruct (Horizon 2020, appel 2019, Consolidator grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Individuals, Markets and Organisations
Entité participante : University of London — Pays : Royaume-Uni — Rôle : PI
Acronyme de l'entité : U. London
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 889090.74 €

Most usable data is unstructured. Examples include text, transaction data, images, and web browsing histories. Although rich and plentiful, most economists do not use unstructured data. The few that do generally quantify it with off-the-shelf algorithms that are unrelated to the economic environment in which it is generated, which makes connecting it to economic models difficult. I instead propose to build novel probabilistic models of unstructured data that link it directly to relevant economic parameters. This powerful approach will use the information in unstructured data to test and estimate economic models in a way that is not currently possible with existing methods. I will focus on three distinct themes. The first studies how information about economic conditions is dispersed among agents, and how they aggregate it through interactions. This process it at the heart of the policymaking process, and the use of text data provides a unique opportunity to structurally model this information in innovative ways. The second theme jointly models unstructured data and the evolution of an economy hit by multiple, unobserved shocks. This will provide a novel forecasting tool, which is of key interest to policymakers. But it will also use unstructured data to estimate equilibrium models of the macroeconomy, and hence recover economic fundamentals. The final theme will use transaction payments between firms, and extend probabilistic models of network formation to create new definitions of markets that go well beyond anything in the current literature. This will contribute to measuring market power and the transmission of economic shocks, both questions of fundamental importance. Beyond these specific themes, my research will also pave the way for the use of probabilistic machine learning that combines novel data with clear economic models. The frameworks I introduce will provide a template for others to follow in the future.

Mots-clés : unstructured data,probabilistic machine learning,bayesian inference,structural modeling
Projet ERC : InfoInt (Horizon 2020, appel 2014, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Systems and communication engineering
Entité participante : Tel Aviv University — Pays : Israël — Rôle : PI
Acronyme de l'entité : TAU
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1323875.0 €

Motivated by our recent progress in feedback information theory and its deep relations to stochastic dynamical systems, and inspired by natural phenomena such as bio-molecular interactions and human conversation, this research will explore the fundamental limits of information transfer via simple interaction. In the standard information theoretic framework, the problem of reliable communications is typically studied in an asymptotic unidirectional regime, where optimal performance is attained via complex codes employed over increasingly long time epochs. Here, we will investigate a markedly different paradigm where communicating parties are restricted to use simple finite-state rules to act and react on the fly. We will consider a broad spectrum of models ranging from feedback communications and two-way channels to multiuser setups and large homogeneous networks, and study measures of information transfer and dissipation, their relations to dynamical system contraction factors, and the fundamental tradeoffs between complexity and performance. While prominently theoretic, our investigation is expected to admit important practical applications and a cross-disciplinary impact. In communications, and especially in resource-limited systems such as wireless sensor networks where battery-life is a bottleneck, a breakthrough in the understanding of optimal interaction can lead to a paradigm shift in system design, yielding simpler, cheaper, more robust solutions. In Finance, where market behavior is a cumulative effect of local actions taken by individuals based on limited noisy observations, quantifying interaction and its relation to information propagation can enhance our ability to forecast and explain macro level phenomena. Finally, an information theoretic characterization of interaction in large networks can shed light on the underlying mechanisms governing various biological systems that are empirically amenable to cellular automata modeling.

Mots-clés : information theory,interactive communications,feedback communications,dynamical systems,posterior matching
Projet ERC : FIRSTORM (Horizon 2020, appel 2015, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Condensed matter physics
Entité participante : Scuola Internazionale Superiore di Studi Avanzati — Pays : Italie — Rôle : PI
Acronyme de l'entité : SISSA
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1422684.0 €

Mott insulators are “unsuccessful metals”, where conduction is impeded by strong Coulomb repulsion. Their use in microelectronics started to be seriously considered in the 1990s, when first reports of field-effect switches appeared. These attempts were motivated by the expectation that the dielectric breakdown in Mott insulators could suddenly release all formerly localized carriers, a significant potential for nanometer scaling. Over the very last years striking experimental data on narrow-gap Mott insulators have finally materialized that expectation disclosing an unprecedented scenario where the metal phase actually stabilized was only metastable at equilibrium, which foreshadows exciting potential applications. These new data call for an urgent theoretical understanding so far missing. In fact, the conventional portrait of Mott insulators has overlooked that Mott transitions are mostly 1st order, implying an extended insulator-metal coexistence. As a result, bias or light may nucleate long-lived metastable metal droplets within the stable insulator, as indeed seen in experiments. The unexpected 1st order nature of dielectric breakdown in Mott insulators and its poorly explored but important conceptual and practical consequences are the scope of my theoretical project. I will model known Mott insulators identifying the variety of mechanisms (Coulomb, lattice distortions) that support and boost the 1st order character of the Mott transition. I will model and study insulator-metal coexistence and associated novel phenomena such as those related to nucleation and wetting at the interface, including possible unexplored role of quantum fluctuations. I will then simulate in model calculations the spatially inhomogeneous dynamics and non-equilibrium pathways across the 1st order Mott transition, relating the results to ongoing experiments in top groups. The outcome of this project is expected to yield immediate conceptual as well as later technological consequences.

Mots-clés : metal insulator mott transitions
Projet ERC : InfoSampCollectJgmt (Horizon 2020, appel 2017, Consolidator grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Social World and Its Diversity
Entité participante : Pompeu Fabra University — Pays : Espagne — Rôle : PI
Acronyme de l'entité : UPF
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1158625.0 €

Much research has shown that judgments are the products of imperfect information processing heuristics. Recently, an alternative theoretical perspective has been proposed. It emphasizes that people form judgments by observing information samples about the alternatives. Sampling-based theories can explain numerous judgment patterns such as risk aversion, overconfidence, illusory correlations, the in-group out-group bias, or social influence. The sampling approach has illustrated how these and other important patterns of human judgments can be parsimoniously explained by assuming a common source of bias. But at least two important questions remain: 1. How do sampling explanations for judgment biases can be integrated with explanations that focus on information-processing biases in order to explain judgment patterns in naturally occurring environments? 2. What are the implications of selective information sampling for collective judgments and the distribution of beliefs and attitudes over social networks? I set to answer these pressing questions by (1) developing integrative belief formation models that incorporate both sampling-based mechanisms and information processing-based mechanisms; (2) collecting and analyzing experimental and field data to test these integrative models and uncover how the two classes of mechanisms interact; (3) building on these insights to develop models that lead to testable predictions about collective judgments and test these predictions with field and experimental data; (4) running experiments to measure the extent to which social network driven information sampling can contribute to opinion polarization. The project will carry novel prescriptions to limit judgment biases such as the prevalence of negative stereotypes about socially distant others or the resistance to institutional change. It will also carry prescriptions to limit the emergence of collective illusions, and contain the polarization of opinions across social groups.

Mots-clés : judgment,collective judgment,wisdom of the crowd,judgment aggregation,learning,attitudes,illusions
Projet ERC : LEAFHOUND (Horizon 2020, appel 2019, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Systems and communication engineering
Entité participante : KTH Royal Institute of Technology — Pays : Suède — Rôle : PI
Acronyme de l'entité : KTH
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1999996.0 €

Multi-agent control is a popular research topic due to its applications in a variety of areas. The main approach has been to incorporate tools from single-agent control to the multi-agent setup. However, many applications involve more complex tasks that may not be cast as a classic control objective, while the agents may be subject to constraints in space and time. A current trend is thus to use formal verification in order to specify more general task specifications that induce a sequence of control actions rather than a stand-alone objective. Spatiotemporal logics are based on continuous time signals and allow formulating space and time constraints, and thus are suitable for defining such specifications in multi-agent systems. Existing solutions do not take into account quantitative transient constraints, nor consider the high computational cost that may be endured by controlling the whole agent group when the number of agents grows. We instead consider here a heterogeneous, leader-follower approach, which relies on three design stages. At a first stage, we derive transient controllers for cooperative control objectives in leader-follower networks; at a second stage, these controllers are employed in order to satisfy tasks given to the network as spatiotemporal logic specifications; and at a third stage, we tackle task dependencies and infeasibilities through a refinement process both in the transient control design as well as in the leader-follower group structure, by using notions of network controllability. The proposed leader-follower approach to the spatiotemporal task planning problem, combining elements from cooperative multi-agent systems under transient constraints, formal verification and graph theoretic network controllability, requires for new ways of thinking and approaches to analysis and design; it thus constitutes the proposal a beyond the SoA and groundbreaking approach to the fields of control, robotics and formal methods based synthesis.

Mots-clés : multi agent control systems,formal methods based control synthesis,multi robot control,leader follower cooperative control,hybrid systems
Projet ERC : MultiQubit (Horizon 2020, appel 2020, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Systems and communication engineering
Entité participante : Technical University of Denmark — Pays : Danemark — Rôle : PI
Acronyme de l'entité : DTU
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2359678.75 €

MultiQubit is built on the concept of a novel type of quantum dots — crystal-phase quantum dots — discovered and developed by the PI. Crystal-phase quantum dots have a unique advantage — growth control with the ultimate accuracy of a single atomic layer. This advantage will break the major limitation in the field of optically-active quantum dots — impossibility to build quantum devices with multiple quantum dots due to lack of the required growth control — and thus unlock their true potential for Quantum Technologies. Based on these, MultiQubit is committed to creating a robust technological platform for making solid-state multi-qubit devices with a photonic interface. This platform shall be a game-changer in Quantum Technologies, allowing to connect quantum computers across the world. In particular, MultiQubit will develop and demonstrate all the steps from the fabrication of basic quantum structures to distributed entanglement between remote nodes of a multi-qubit Quantum Information Network. For the successful realization of these ideas, the PI proposes three key objectives: 1. Explore and demonstrate a novel crystal-phase qubit — the central element of MultiQubit. This qubit is based on crystal-phase quantum dots, which are fully designable and scalable, because their geometry can be controlled with the ultimate accuracy of a single atomic layer during the growth. 2. Build the first designable and scalable multi-qubit quantum register with a photonic interface. This is one of the major components in Quantum Information Networks to be implemented. 3. Design and demonstrate a quantum network of multi-qubit photonic devices. This may be a potential prototype of the forthcoming Quantum Internet.

Mots-clés : quantum information networks,quantum dots,nanowires,quantum nanophotonics
Projet ERC : ETAP (Horizon 2020, appel 2016, Advanced grants)
Domaine scientifique : Life Science
Panel : Cellular, Developmental and Regenerative Biology
Entité participante : Institute of Science and Technology Austria — Pays : Autriche — Rôle : PI
Acronyme de l'entité : ISTA
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2410292.0 €

Multicellularity in plants evolved independently from other eukaryotes and presents a unique, alternative way how to deal with challenges of life. A major plant developmental module is the directional transport for the plant hormone auxin. The crucial components are PIN auxin transporters, whose polar, subcellular localization determines directionality of auxin flow through tissues. PIN-dependent auxin transport represents a unique model for studying the functional link between basic cellular processes, such as vesicle trafficking and cell polarity, and their developmental outcome at the level of the multicellular organism. Despite decades of intensive research, the classical approaches in the established models are approaching their limits and many crucial questions remain unsolved, in particular related to PIN structure, regulatory motifs and evolutionary origin I propose to start a new direction in my research using an evolutionary perspective. This promises to overcome current limitations and provides not only (i) interesting insights into PIN evolution and diversification, but also (ii) a unique opportunity to study how evolutionary conserved cellular mechanisms of e.g. endocytic trafficking evolved specific plug-ins to make them subject to plant-specific regulations. The characterization of (iii) prokaryotic PIN origin will provide a so urgently needed (iv) entry into PIN structural studies. To achieve these goals, we will also establish novel (v) genetic and cell biological models in the ancestral lineage of the land plants that will be of a great use for any plant evolutionary studies. The intellectual and methodological challenges of such interdisciplinary strategy combining several lower and higher plant models are obvious, but our preliminary results at several fronts promise its feasibility and success to gain deeper understanding of exciting questions on evolution and mechanisms behind the coordination and specification of developmental programs.

Mots-clés : plant evolution,auxin transport,pin auxin transporters,adaptive development,cell polarity,subcellular trafficking,tissue patterning,growth responses,signalling molecules
Projet ERC : SPACE4AMPS (Horizon 2020, appel 2019, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Synthetic Chemistry and Materials
Entité participante : University of Bern — Pays : Suisse — Rôle : PI
Acronyme de l'entité : UB
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2495285.0 €

Multidrug resistant (MDR) bacteria represent a global public health threat against which new drugs are urgently needed. Antimicrobial peptides (AMPs), mostly derived from naturally occurring linear or cyclic peptides, can contribute to solving the problem. AMPs are already in clinical use, do not easily lead to resistance, and can rely on a strong manufacturing sector and established protocols for clinical development. However, most AMPs are degraded by proteases and have poor pharmacokinetics. SPACE4AMPS aims to identify new AMPs with diverse peptide chain topologies and building blocks and with the following characteristics: i) Broad activity spectrum, ii) High activity, iii) Low probability for induced resistance, iv) Low proteolysis, v) Better pharmacokinetics. To reach its goal SPACE4AMPS will create computational tools to explore the extremely vast chemical space of large molecules such as peptides and natural products, which now lies within reach of the latest computer hardware developments. To better understand antimicrobial drugs, we will design a molecular fingerprint relating antimicrobial activity to molecular structure and use it to draw a tree-map of the antimicrobial chemical space. We will enrich this map with new compounds from generative models using neural networks. To identify new AMPs, we will use a genetic algorithm carrying out cycles of molecule generation and similarity calculations to select cyclic peptides and peptide dendrimers including lipidated, peptoid (N-alkyl glycines) and N-methylated residues, synthesize and test these molecules against MDR bacteria, fungi and parasites, screen actives for toxicity, and study their structure and mode of action. By its ground-breaking and unprecedented computational/synthetic/biological approach, SPACE4AMPS can help solve the antibiotics crisis, revolutionize knowledge on antimicrobial compounds, and create new methods enabling computer-aided drug discovery for large molecules.

Mots-clés : cheminformatics,data visualization,machine learning,drug discovery,peptides,dendrimers,peptoids,diversity oriented synthesis
Projet ERC : COSMOS (Horizon 2020, appel 2017, Advanced grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Cultures and cultural production
Entité participante : Centre national de la recherche scientifique — Pays : France — Rôle : Partner
Acronyme de l'entité : CNRS
Type d'entité : Recherche
Financement ERC de l'entité : 985054.53 €

Music performance is considered by many to be one of the most breath taking feats of human intelligence. That music performance is a creative act is no longer a disputed fact, but the very nature of this creative work remains illusive. Taking the view that the creative work of performance is the making and shaping of music structures, and that this creative thinking is a form of problem solving, COSMOS proposes an integrated programme of research to transform our understanding of the human experience of performed music, which is almost all music that we hear, and of the creativity of music performance, which addresses how music is made. The research themes are as follows: i) to find new ways to represent, explore, and talk about performance; ii) to harness volunteer thinking (citizen science) for music performance research by focussing on structures experienced and problem solving; iii) to create sandbox environments to experiment with making performed structures; iv) to create theoretical frameworks to discover the reasoning behind the structures perceived and made; and, v) to foster community engagement by training experts to provide feedback on structure solutions so as to increase public understanding of the creative work in music performance. Analysis of the perceived and designed structures will be based on a novel duality paradigm that turns conventional computational music structure analysis on its head to reverse engineer why a perceiver or a performer chooses a particular structure. Embedded in the approach is the use of computational thinking to optimise representations and theories to ensure accuracy, robustness, efficiency, and scalability. The PI is an established performer and a leading authority in music representation, music information research, and music perception and cognition. The project will have far reaching impact, reconfiguring expert and public views of music performance and time-varying music-like sequences such as cardiac arrhythmia.

Mots-clés : music performance studies,music perception and cognition
Projet ERC : HYPER-INSIGHT (Horizon 2020, appel 2017, Starting grants)
Domaine scientifique : Life Science
Panel : Integrative Biology: from Genes and Genomes to Systems
Entité participante : Institute for Research in Biomedicine — Pays : Espagne — Rôle : PI
Acronyme de l'entité : IRB;IRB-CERCA
Type d'entité : Recherche
Financement ERC de l'entité : 1499812.5 €

Mutations are the fuel of any evolutionary process, and this also applies to carcinogenesis. The advent of affordable DNA sequencing has enabled mutagenic processes in the human soma to be quantified genome-wide, revealing a striking occurrence of hypermutated tumors. They exhibit an extreme load of somatic changes, often harbouring hundreds of single-nucleotide variants and/or indels per megabase. The HYPER-INSIGHT project is organized into three objectives, which aim to take advantage of the unique opportunity provided by genome sequences of hypermutated and ultramutated tumors. In particular, this work planned in this project aims to further our knowledge on (i) the regional organization of the DNA replication and repair program in human cells, and the determinants thereof, (ii) the extent of selection which acts on somatic variants in various pathways or complexes and (iii) opportunities for selectively targeting DNA repair deficiencies that manifest as hypermutation. Methodologically, our work will employ a three-pronged approach. First, we will perform a multitude of rigorous statistical analyses that draw on the rich and still-expanding resources provided by cancer genomics consortia. Second, we will perform exome and genome sequencing, focusing on ultramutated tumors caused by specific defects in the DNA maintenance machinery. Third, the project involves conditional essentiality screens on cancer cell lines with hypermutant backgrounds. Their goal is to discover synthetic lethality relationships, useful for targeting hypermutating cells, while sparing healthy ones. In summary, one of the promises of cancer genome sequencing projects was to elucidate the mechanisms underlying mutational processes in the human soma, advancing our understanding of this important facet of cancer biology. We will work towards realizing this promise, thereby strengthening the EU’s position in the global scientific endeavour.