Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : 123STABLE (Horizon 2020, appel 2019, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Physical and analytical chemical sciences
Entité participante : National Institute of Chemistry — Pays : Slovénie — Rôle : PI
Acronyme de l'entité : NIC;KI
Type d'entité : Recherche
Financement ERC de l'entité : 1364750.0 €

In the last decades, significant progress has been made on understanding and controlling solid/liquid electrochemical interfaces at atomic levels. As the principles guiding the activity of electrochemical reactions are quite well established (structure-activity relationships), the fundamentals of stability are still poorly understood (structure-stability relationships). 123STABLE proposes to employ (1) identical location, (2) online monitoring and (3) modeling of noble metals based nanoparticles changes with the state-of-the-art electron microscopy equipment and online dissolution and evolution analytics using electrochemical flow cell coupled to online mass spectrometers. Projects unique methodology approach with picogram sensitivity levels, in combination with sub-atomic scale microscopy insights and simulations, promises novel atomistic insights into the corrosion and reconstruction of noble metals in electrochemical environments. This unique approach is based on observations of the same nanoparticles before and after electrochemical treatment where weak and stable atomic features and events can be recognized, followed, understood and finally utilized. Upon (1) doping, (2) decoration and/or (3) other synthetic modification of nanoparticles like a change in size and shape further stabilization is envisioned. For instance, blockage of nanoparticle vulnerable defected sites like steps or kinks by more noble metal could stop or significantly slow down their degradation. The 123STABLE project will feature platinum- and iridium-based nanostructures as a model system to introduce a unique “123” approach, as they still possess the best electrocatalytic properties for the future electrification of society through the Hydrogen economy. However, their electrochemical stability is still not sufficient. Coupled with the fact that their supply is hindered by extremely scarce, rare and uneven geological distribution, the increase in their stability is of immense importance.

Mots-clés : electrocatalysis,degradation,fuel cells,electrolyzers,electron microscopy,development of advanced electrochemical characterisation methods
Projet ERC : PHONUIT (Horizon 2020, appel 2017, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Condensed matter physics
Entité participante : University of Basel — Pays : Suisse — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1488387.5 €

In the last decades, the power to control photons and electrons paved the way for extraordinary technological developments in electronic and optoelectronic applications. The same degree of control is still lacking with quantized lattice vibrations, i.e. phonons. Phonons are the carriers of heat and sound. The understanding and ability to manipulate phonons as quantum particles in solids enable the control of coherent phonon transport, which is of fundamental interest and could also be exploited in applications. Logic operations can be realized with the manipulation of phonons both in their coherent and incoherent form in order to switch, amplify, and route signals, and to store information. If brought to a mature level, phononic devices can become complementary to the conventional electronics, opening new opportunities. I envision to realize each part of this technology exploiting phonons and to bring them together in an integrated circuit on chip: a phononic integrated circuit. The objective of the proposal is: A: the realization of coherent phonon source and detector; B: the realization of phonon computation with the use of thermal logic gates; C: the realization of phonon based quantum and thermal memories. To this end it is crucial to engineer nanoscale heterostructures with suitable interfaces, and to engineer the phonon spectrum and the interface thermal resistance. Phonons will be launched, probed and manipulated with a combination of pump-probe experiments and resistive thermal measurements on chip. The proposed research will be of great relevance for fundamental research as well as for technological applications in the field of sound and thermal management.
Projet ERC : MARKET POWER (Horizon 2020, appel 2019, Advanced grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Individuals, Markets and Organisations
Entité participante : Barcelona Graduate School of Economics — Pays : Espagne — Rôle : Partner
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 125000.0 €

In the last four decades, there have been a number of significant secular trends in the advanced economies around the world. Wage inequality has risen sharply, and most of the wage gains have been appropriated by the top 1%. In addition, labor market dynamism and new startups have declined, the labor share of total output has fallen, low skilled wages have stagnated, and there has been reallocation of production from small to superstar firms. During the same four decades, there has also been a sharp secular increase in market power. Firms set higher prices, profit rates are higher, and scale economies are up. In this proposal, I address the question whether these secular trends are related. Specifically, I ask whether the rise of market power has caused these profound macroeconomic changes. The objective is to uncover economic mechanisms that help understand this fundamental transformation and the implications for efficiency and welfare. I propose to investigate both the causes of the rise in market power and its macroeconomic consequences. I distinguish between causes that stem inherently from the market structure (such as antitrust enforcement and Mergers & Acquisitions) and those that result from technological change (economies of scale, intangible assets, and network externalities). Methodologically, this research proposal aims to contribute to the literature on three fronts: 1. the measurement of markups, 2. to derive theoretical results linking market power and macroeconomic consequences, 3. to estimate and quantitatively evaluate these models. The close link between the macroeconomic consequences and the causes of market power renders this a research proposal at the intersection of macro/labor, industrial organization and law & economics. The objective is to inform the policy debate: how to keep market power under control in order to remediate its macroeconomic consequences that were hitherto considered independent.
Projet ERC : BroadSem (Horizon 2020, appel 2015, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Computer science and informatics
Entité participante : University of Amsterdam — Pays : Pays-Bas — Rôle : Partner
Acronyme de l'entité : UvA
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 167242.5 €

In the last one or two decades, language technology has achieved a number of important successes, for example, producing functional machine translation systems and beating humans in quiz games. The key bottleneck which prevents further progress in these and many other natural language processing (NLP) applications (e.g., text summarization, information retrieval, opinion mining, dialog and tutoring systems) is the lack of accurate methods for producing meaning representations of texts. Accurately predicting such meaning representations on an open domain with an automatic parser is a challenging and unsolved problem, primarily because of language variability and ambiguity. The reason for the unsatisfactory performance is reliance on supervised learning (learning from annotated resources), with the amounts of annotation required for accurate open-domain parsing exceeding what is practically feasible. Moreover, representations defined in these resources typically do not provide abstractions suitable for reasoning. In this project, we will induce semantic representations from large amounts of unannotated data (i.e. text which has not been labeled by humans) while guided by information contained in human-annotated data and other forms of linguistic knowledge. This will allow us to scale our approach to many domains and across languages. We will specialize meaning representations for reasoning by modeling relations (e.g., facts) appearing across sentences in texts (document-level modeling), across different texts, and across texts and knowledge bases. Learning to predict this linked data is closely related to learning to reason, including learning the notions of semantic equivalence and entailment. We will jointly induce semantic parsers (e.g., log-linear feature-rich models) and reasoning models (latent factor models) relying on this data, thus, ensuring that the semantic representations are informative for applications requiring reasoning.

Mots-clés : natural language processing
Projet ERC : GoodNews (Horizon 2020, appel 2018, Proof of concept grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Computer science and informatics
Entité participante : Università della Svizzera italiana — Pays : Suisse — Rôle : PI
Acronyme de l'entité : USI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 150000.0 €

In the past decade, social media have become one of the main sources of news for people around the world. Yet, it comes with the danger of exposure to intentionally false information. The extensive spread of fake news has recently become a centerpiece of controversy following the highly debated elections of President Donald Trump and the Brexit vote. It is alleged that the outcome of these votes resulted from the public opinion manipulation by a massive injection of fake news, possibly sponsored by hostile foreign governments, constituting perhaps one of the most serious and unprecedented threats to the modern democracies. The ambition of GoodNews is to build the technological capability for algorithmic fake news detection in social media using a novel paradigm. Instead of following the traditional approach of analyzing the news content, we will analyze the news spreading patterns in social networks. The algorithmic core of GoodNews is based on a novel class of geometric deep learning algorithms developed in the ERC project LEMAN (Learning on Manifolds and Graphs). Our research group was among the first in the world to propose, implement, and patent generalizations of popular convolutional neural network architectures to graph-structured data such as social networks, allowing to do deep learning on graphs. The ability to learn fake news spread patterns on social networks will provide the needed breakthrough in the task of automated fake news detection. GoodNews will convert the geometric deep learning technology into a commercial application of fake news detection in social media. The focus of the project will be three-fold: developing a demo system for fake news detection with real data from social media; verifying and solidifying our IP portfolio and its licensing terms; analyzing the market and coming up with a financeable business plan. We target establishing a company at the end of the project and attracting investment to develop a commercial-grade product.

Mots-clés : fake news detection,social media,social network analysis,geometric deep learning,deep learning on graphs
Projet ERC : DISINTEGRATION (Horizon 2020, appel 2018, Consolidator grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Institutions, Governance and Legal Systems
Entité participante : University of Zurich — Pays : Suisse — Rôle : PI
Acronyme de l'entité : UZH
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1998626.0 €

In the past few years, there has been a growing popular backlash against international institutions. Examples include the 2015 Greek bailout referendum, the 2016 Brexit referendum, or the 2016 election of a US President seemingly determined to withdraw US support from various international treaties. The implications of these mass-based disintegration efforts reach far beyond the countries in which they originate. First, the disintegration process is shaped by how remaining member states respond to one member’s bid to unilaterally change or terminate the terms of an existing international agreement. Second, mass-based disintegration bids pose considerable political contagion risks by encouraging disintegrative tendencies in other countries. Unfortunately, our theoretical tools to understand such international disintegration processes are underdeveloped. DISINTEGRATION therefore conducts a broad, systematic, and comparative inquiry into the mass politics of disintegration that pays particular attention to reactions in the remaining member states. It explores when and how one country’s mass-based disintegration experience encourages or deters demands for disintegration in other countries, how these contagion effects are transmitted through domestic elites and domestic discourse, and how the remaining member states ultimately respond during disintegration negotiations. It undertakes large-scale multi-method data collection that exploits the research opportunities offered by two ongoing mass-based disintegration processes: the Brexit negotiations and an upcoming Swiss referendum aimed at terminating a Swiss-EU bilateral treaty. DISINTEGRATION’s main objective is to develop a much-needed theory of mass-based disintegration that helps us understand the transnational dynamics that unfold between governments, political elites and the mass public when one member state attempts to unilaterally withdraw from an international agreement on the basis of widespread popular support.

Mots-clés : political science,disintegration,public opinion,referendums,international cooperation,european union,euroscepticism,international negotiations,contagion,trade offs,international organization
Projet ERC : FAIME (Horizon 2020, appel 2019, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Fundamental constituents of matter
Entité participante : University of Ljubljana — Pays : Slovénie — Rôle : Partner
Acronyme de l'entité : UL
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 494703.75 €

In the proposed research, precision measurements of rare processes involving heavy quarks and leptons will be used to search for new phenomena beyond the Standard Model, popularly known as New Physics. This research at the intensity frontier is complementary to searches at the highest achievable energies carried out at the LHC proton-proton collider. Indications of very interesting discrepancies have recently been observed by three experiments (LHCb, BaBar, and Belle) between their results and predictions of the Standard Model in certain classes of decays of B mesons, which involve leptons in the final state. The proposed project will address these issues by using large event samples collected with the Belle II detector at a new electron-positron collider, SuperKEKB. By investigating a broad range of selected rare decays of B and D, the project will attempt to provide a definite answer on the violation of Lepton Flavour Universality, one of the cornerstones of our current understanding of the interactions among the elementary particles. Based on the results of these studies, the final stages of the project will be devoted to possible explanations and to studies of transitions that would be based on related new physics phenomena. Within the proposed research programme, novel, highly advanced identification methods for charged particles will also be developed. They will be of crucial importance to suppress backgrounds arising from other, much more abundant decays in measurements of rare processes where the sensitivity to a possible contribution of New Physics is largest. The proposed research will strongly benefit from the fact that the same group that contributed substantially to the physics programme, concept, design, and construction of the detector, will also carry out the development of novel analysis methods, their calibration and optimization for individual reactions.

Mots-clés : flavour physics,flavour anomalies,lepton universality,belle ii,superkekb
Projet ERC : RedLang (Horizon 2020, appel 2020, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Mathematics
Entité participante : Technical University of Darmstadt — Pays : Allemagne — Rôle : Partner
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 350090.0 €

In the recent years the PI has been involved in several breakthrough results in the representation theory of reductive algebraic groups (in particular related to the computation of character formulas for simple and indecomposable tilting modules), obtained using various techniques (in particular geometry and categorification). The present proposal aims at: 1. exploring the new perspectives offered by these results, which go beyond the computation of characters, and by the techniques we have already developed; 2. developing new geometric tools to support these advances. Our main geometric input will be the development of a modular Local Geometric Langlands duality, in the spirit of work of Bezrukavnikov for characteristic-0 coefficients, and of a modular "ramified" geometric Satake equivalence. We expect in particular applications in the study of tilting modules (e.g. their behaviour under restriction to reductive subgroups, and their multiplicative properties), and to the description of the center of the distribution algebra (with a view towards understanding the "higher linkage" phenomena).

Mots-clés : representation theory,perverse sheaves
Projet ERC : RedLang (Horizon 2020, appel 2020, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Mathematics
Entité participante : Université Clermont Auvergne — Pays : France — Rôle : PI
Acronyme de l'entité : UCA
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 918461.0 €

In the recent years the PI has been involved in several breakthrough results in the representation theory of reductive algebraic groups (in particular related to the computation of character formulas for simple and indecomposable tilting modules), obtained using various techniques (in particular geometry and categorification). The present proposal aims at: 1. exploring the new perspectives offered by these results, which go beyond the computation of characters, and by the techniques we have already developed; 2. developing new geometric tools to support these advances. Our main geometric input will be the development of a modular Local Geometric Langlands duality, in the spirit of work of Bezrukavnikov for characteristic-0 coefficients, and of a modular "ramified" geometric Satake equivalence. We expect in particular applications in the study of tilting modules (e.g. their behaviour under restriction to reductive subgroups, and their multiplicative properties), and to the description of the center of the distribution algebra (with a view towards understanding the "higher linkage" phenomena).

Mots-clés : representation theory,perverse sheaves
Projet ERC : AlgoQIP (Horizon 2020, appel 2019, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Computer science and informatics
Entité participante : Institut national de recherche en sciences et technologies du numérique — Pays : France — Rôle : PI
Acronyme de l'entité : Inria
Type d'entité : Recherche
Financement ERC de l'entité : 1492733.0 €

In the road towards quantum technologies capable of exploiting the revolutionary potential of quantum theory for information technology, a major bottleneck is the large overhead needed to correct errors caused by unwanted noise. Despite important research activity and great progress in designing better error correcting codes and fault-tolerant schemes, the fundamental limits of communication/computation over a quantum noisy medium are far from being understood. In fact, no satisfactory quantum analogue of Shannon’s celebrated noisy coding theorem is known. The objective of this project is to leverage tools from mathematical optimization in order to build an algorithmic theory of optimal information processing that would go beyond the statistical approach pioneered by Shannon. Our goal will be to establish efficient algorithms that determine optimal methods for achieving a given task, rather than only characterizing the best achievable rates in the asymptotic limit in terms of entropic expressions. This approach will address three limitations — that are particularly severe in the quantum context — faced by the statistical approach: the non-additivity of entropic expressions, the asymptotic nature of the theory and the independence assumption. Our aim is to develop efficient algorithms that take as input a description of a noise model and output a near-optimal method for reliable communication under this model. For example, our algorithms will answer: how many logical qubits can be reliably stored using 100 physical qubits that undergo depolarizing noise with parameter 5%? We will also develop generic and efficient decoding algorithms for quantum error correcting codes. These algorithms will have direct applications to the development of quantum technologies. Moreover, we will establish methods to compute the relevant uncertainty of large structured systems and apply them to obtain tight and non-asymptotic security bounds for (quantum) cryptographic protocols.

Mots-clés : information theory,optimization
Projet ERC : Vis4Weather (Horizon 2020, appel 2016, Proof of concept grants)
Entité participante : Technical University of Munich — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : TUM
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 148750.0 €

In the scope of my ERC Advanced Grant “SaferVis", I have focused especially on the development of novel concepts and algorithms for analysing the uncertainty that is represented by an ensemble of simulations of a physical phenomenon, such as ensemble weather forecasts. Instead of making a single deterministic computation of the future weather state, today the weather centres worldwide compute ensembles of numerical forecasts routinely using operational ensemble prediction systems. Weather forecasts then take the form of probabilities of occurrence of weather events, which are derived from the ensemble fields. In the scope of SaferVis we have developed the opensource software tool Met.3D for 3D meteorological ensemble visualization. In the PoC, I aim to study a) the potential of an operational use of Met.3D at weather centres, b) the potential of Met.3D for training forecasters, decision makers and researchers in 3D ensemble visualization, c) the possible societal impact of (3D) ensemble visualization for communicating uncertainty in forecasts of high impact weather events to the public, and d) Met.3D’s potential for commercialization.

Mots-clés : ensemble based weather forecasting,high impact weather communication,societal impact