Mohamed Amara is a full-time Professor at the University of Pau and the Pays de l'Adour (UPPA) since 1996, affiliated with the Laboratory of Mathematics and their Applications (CNRS-UMR 5142). He served as its director (1999-2007), Director of the Doctoral School of Exact Sciences (ED211, 2007-2008), and UPPA's Scientific Council Vice-President (2008-2012). He has been UPPA's President since 2012 (re-elected until 2020). Education: Mathematics from University of Algiers (1973), Pierre and Marie Curie University (DEA 1974, Doctorate 1978, State Doctorate 1983) Academic Roles: Research Associate at Ecole Polytechnique (1978-1982), Algerian Electricity and Gas Company (1983-1992), Professor in Algiers (1988-1994), Tunis (1994-1995), and Associate Professor at Paris 6 (1995-1996) His research focuses on numerical simulation of partial differential equations for environmental/energy applications, including mechanics in porous media (petroleum engineering, geoscience), fluid mechanics (aerodynamics, estuarine hydrodynamics), non-Newtonian flows, and wave propagation. Articles highlight expertise in discontinuous Galerkin methods, Helmholtz problems, finite element discretization, and multiphysics systems. He managed 20 doctoral theses and led national mathematics programs at ANR (2007-2011). He chairs the Cocktail association for higher education IT systems and collaborates with INRIA's Magique 3D team (since 2006).
Yvain Bruned is a Professor of Mathematics at Université de Lorraine, Nancy, France, where he leads research in singular stochastic partial differential equations and related fields. He serves as Principal Investigator for the ERC Starting Grant LoRDeT (2023-2028), which focuses on advancing the theory of decorated trees and Hopf algebraic structures for solving singular SPDEs and dispersive PDEs at low regularity. Previously, he was a Lecturer at the University of Edinburgh (2019-2022) and completed postdoctoral work at Imperial College London and University of Warwick under Martin Hairer. His educational background includes: PhD in Mathematics (2012-2015), UPMC (Paris 6), on "Singular KPZ type equations" under Lorenzo Zambotti Master 2 in Probability and Statistics, ENS Cachan / Rennes 1, with honors Master 1 in Mathematics, ENS Cachan, with honors Bachelor in Mathematics and Computer Science, University of Rennes 1, with honors Student at ENS Cachan Brittany extension (2009-2013) Classes Préparatoires in Mathematics and Physics (2007-2009) Bruned's research centers on singular stochastic partial differential equations, with particular focus on Regularity Structures, renormalization theory, and their connections to Hopf algebras. His work bridges theoretical mathematics with applications in quantum field theory, wave turbulence, and numerical analysis. He has developed novel approaches using decorated trees to handle renormalization procedures for singular SPDEs and has extended these methods to dispersive PDEs with random initial data. His research program aims to establish existence and uniqueness results for quasilinear and dispersive SPDEs while developing algebraic tools through deformations of Hopf algebras. His extensive publication record demonstrates consistent contributions to the field of singular SPDEs, with a clear trajectory from foundational work on Regularity Structures to more recent applications in dispersive PDEs and numerical methods. The publications reveal a strong collaborative network with leading researchers in stochastic analysis, mathematical physics, and algebra. His work shows increasing sophistication in handling renormalization procedures through algebraic structures, with recent papers exploring connections between different mathematical frameworks. His major scientific recognition includes: ERC Starting Grant LoRDeT (2023-2028) Bruned actively supervises a large group of researchers, currently advising 4 PhD students and 2 postdoctoral researchers at Université de Lorraine, with several former PhD students having completed their degrees at the University of Edinburgh. His ERC grant has enabled him to organize multiple international workshops in Nancy, fostering collaboration between researchers in singular SPDEs, algebraic structures, and numerical analysis. The grant also supports the development of software platforms for decorated trees and their Hopf algebraic structures. As Principal Investigator of the ERC LoRDeT project, Bruned leads a vibrant research team based at the Elie Cartan Institute of Lorraine, which includes postdocs, PhD students, and visiting researchers. The team regularly organizes specialized workshops on topics including operads, symmetries for quantum field theory, and normal forms for singular dynamics, creating a dynamic research environment that bridges multiple mathematical disciplines.
Teresa Faucon is an Associate Professor and HDR researcher at Sorbonne Nouvelle University (Paris 3), affiliated with the IRCAV research institute. She specializes in cinema and audiovisual aesthetics, montage theory, and postcolonial film studies. Her roles include director of the Cinema and Audiovisual Master's program (2021–2023), and leadership in disability and professional training initiatives. She co-founded key research groups like Indian Cinemas (2012), CREAViS (2015), and Exotismes en champ-contrechamp (2018), focusing on decolonial cinema and exoticism analysis. Her work bridges academic research with creative projects, including the interactive Maps of Film Analysis platform. Research interests span Indian and Southeast Asian cinemas, dance-cinema interactions, and experimental film forms. She has organized 7 international conferences and co-edited major texts like Chorégraphier le film (2019). Recent publications include studies on exoticism's sonic dimensions and non-European cinema. Her digital platform Les cartes de l'analyse de film innovates in nonlinear film analysis through heuristic maps. She co-directs the Formes filmiques and Cinémas en champ-contrechamp book series, promoting global cinema scholarship.
Alain Durmus is a Professor at École Polytechnique, affiliated with the applied mathematics department (CMAP). His research focuses on computational statistics, machine learning, and stochastic methods, including Monte Carlo algorithms, Bayesian inference, and optimization. He explores topics such as Markov chain Monte Carlo (MCMC), stochastic approximation, and generative models. His work emphasizes theoretical guarantees for algorithms like Langevin Monte Carlo and Hamiltonian Monte Carlo, with applications to high-dimensional Bayesian inference and inverse problems. Key contributions include hypocoercivity analysis of piecewise deterministic MCMC processes, convergence guarantees for stochastic gradient methods, and the development of efficient sampling techniques. He has also contributed to Bayesian imaging and federated learning through works like the QLSD algorithm. Awarded the Best Student Paper Award at ICASSP 2020 for his work on the Sliced-Wasserstein distance. His teaching spans mathematical statistics, stochastic methods, and probability at École Polytechnique and ENS Paris-Saclay. He has also contributed to conferences and workshops on topics ranging from MCMC convergence to optimization in machine learning.
Guillaume Chiavassa is a Professor in Applied Mathematics at Ecole Centrale de Marseille, affiliated with the Laboratoire M2P2 (Mechanics, Modeling and Physical Processes Laboratory). He leads research in the Thermodynamics, Waves, Digital, Interfaces and Combustion team, focusing on advanced computational methods for complex physical phenomena. His research spans wave propagation in porous media, numerical modeling of plasma flows in Tokamak configurations, multilevel schemes for conservation laws, penalization methods for compressible flows, and wavelets in numerical analysis. Chiavassa's work demonstrates exceptional mathematical rigor applied to challenging physical systems, particularly in nonlinear wave dynamics and computational fluid mechanics. His methodologies bridge theoretical mathematics with practical engineering applications. Analysis of his recent publications reveals a strong focus on wave propagation phenomena across diverse media, with significant contributions to numerical methods for nonlinear systems. His work consistently addresses the mathematical challenges of modeling complex physical behaviors including material softening, fractional attenuation in porous media, and plasma dynamics in fusion devices. The interdisciplinary nature of his research connects applied mathematics with mechanical engineering, geophysics, and nuclear fusion technology. Chiavassa leads the PROSPERO Software project and participates in the ANR Espoir research initiative and the Consortium SEISCOPE. His teaching activities include courses on hyperbolic equations, finite elements, and heat transfer, with practical computational components developed for student instruction. He maintains an active research program through Laboratory M2P2, where his team develops advanced numerical methods for simulating complex physical phenomena with applications ranging from environmental engineering to nuclear fusion research.
Slava Rychkov is a Permanent Professor of Theoretical Physics at the Institut des Hautes Études Scientifiques (IHES), a position he has held since 2017. He specializes in strongly coupled quantum and conformal field theories, with applications across high energy physics, statistical mechanics, and condensed matter physics. His current research focuses on the conformal bootstrap and renormalization group techniques, including both perturbative and nonperturbative methods like tensor network renormalization. Education: Ph.D. in Physics, Princeton University (2002) Master of Science, Moscow Institute of Physics and Technology (1996) Recent research highlights include a groundbreaking connection between Deligne categories and symmetries of probabilistic loop ensembles in statistical physics, and a novel method for analytic continuation of Euclidean CFTs to Lorentzian signature. His work on the 2+ϵ expansion challenges established assumptions about critical exponents in 3D systems. Publications span topics from tensor renormalization group methods to rigorous mathematical approaches in the conformal bootstrap program. Scientific Awards: Jacques Solvay International Chair in Physics (2025) Grand Prix Mergier-Bourdeix, French Academy of Sciences (2019) New Horizons in Physics Prize (2014) As Deputy Director of the Simons Collaboration on the Nonperturbative Bootstrap, Rychkov leads efforts to rigorously analyze conformal field theories. His former advisees include prominent researchers at institutions like EPFL, Princeton, and Università di Genova. Current projects focus on resolving fundamental questions about critical phenomena and phase transitions using advanced mathematical physics tools.
LIN Yaochen is a Lecturer affiliated with the University of Strasbourg, France. He is a member of the MATISEN Team (Materials for information technology, sensors, and energy conversion) at ICube laboratory, where he contributes to research and teaching in materials science and optoelectronics. Role: Lecturer Research Focus: Photovoltaic materials, liquid crystal devices, nanomaterials for energy conversion Teaching: Involved in multiple Master's programs including Micro/Nano-Electronics, Condensed Matter and Nanophysics, and Materials Science Research Interests LIN's work centers on photovoltaic spatial light modulators , self-powered smart windows , and liquid crystal-nanoparticle composites . His research explores material selection, processing techniques, and device optimization to enhance performance in energy conversion and optical modulation. Key areas include: Material synthesis (e.g., TiO2/MWCNT nanohybrids) Charge transport in liquid crystals Dielectric properties of nanocolloids Smart glass technology Atomic-scale modeling of materials Scientific Awards No specific awards mentioned in available texts. Advising & Collaborations Supervises Master's level internships Active in interdisciplinary projects with physics and engineering departments Focuses on material innovation for optoelectronic devices
Yohan PETETIN is an Associate Professor at Telecom SudParis (Institut polytechnique de Paris) in the CITI Department. His research focuses on Bayesian filtering, Monte Carlo methods, hidden Markov models, and multi-object tracking. He has authored over 20 peer-reviewed articles since 2011, with notable contributions in IEEE Transactions on Signal Processing and other top venues. His work bridges statistical signal processing with machine learning applications. PhD: Algorithmes de restauration bayésienne mono- et multi-objets dans des modèles Markoviens (2013, Telecom SudParis) HDR: Generative models for time series data (2023, Institut polytechnique de Paris) Research interests emphasize sequential Monte Carlo algorithms, particle filtering optimizations, and deep learning integration for time-series analysis. Recent work explores expressivity comparisons between recurrent neural networks and hidden Markov models. Teaching includes courses on probabilistic graphical models, Bayesian filtering, and deep learning across undergraduate and graduate programs at Telecom SudParis and affiliated institutions.
Francesco Russo is a Professor of Exceptional Class at ENSTA Paris under the Applied Mathematics Unit (UMA) . He has held academic positions at INRIA-Ecole des Ponts (2008-2010) and Paris 13 University (1994-2008) , where he led the Probability and Statistics Team and the Financial Engineering Option in the MACS course. His research spans Stochastic Analysis , Financial Mathematics , and Probabilistic Models in Mathematical Physics , with applications to energy systems, control theory, and nonlinear PDEs. He co-organizes international seminars and conferences, including the Seminar in Probability-Statistics-Control and the Day Around Stochastic PDEs . Research Themes : Stochastic calculus via regularization, path-dependent PDEs, BSDEs, non-semimartingale models, fractional Brownian motion, and McKean-Vlasov equations with irregular coefficients. Projects : Leads the SDAIM (2023-27) project funded by ANR (France) and FAPESP (Brazil). Coordinated the ANR MASTERIE (2011-2013) program. Teaching : Courses include Elementary Stochastic Calculus (ENSTA), Discrete Models in Finance (ENSTA), and Stochastic Calculus (Master Paris-Saclay). Collaborations : Organizes seminars with institutions such as Luiss University (Rome) and EPFL (Lausanne). Collaborates with Brazilian teams (UNICAMP) and French institutions (CMAP, CentraleSupélec).
Masao Fukushima is a Professor at the Department of System and Mathematical Sciences within the Faculty of Science and Engineering at Nanzan University, Japan. His research focuses on advanced optimization methodologies, including nonlinear programming, variational inequalities, and stochastic optimization. He holds editorial roles in academic journals and was recognized as a 2010 ISI Highly Cited Researcher in Mathematics. His work emphasizes theoretical development and algorithmic innovation in optimization fields such as complementarity problems and equilibrium-constrained programming. Research Interests: Nonlinear Programming Parallel Optimization Algorithms Global and Stochastic Optimization Mathematical Programs with Equilibrium Constraints Nonsmooth Optimization Editorial Activities: Maintains editorial board memberships as of July 2017. No specific grants or labs are detailed in the provided text, though his academic profile reflects sustained contributions to optimization theory and applications.
Alain Trouvé is a Professor at the Center for Mathematics and Their Applications (CMLA) within the Ecole Normale Supérieure de Cachan , France. His research focuses on Shape Spaces , Computational Anatomy , Imaging Processing , and Biological Imaging , with applications in medical and computational fields. He directs the Mathematics Department at ENS Cachan and contributes to neuroanatomical studies through diffeomorphometry techniques. Key roles include membership in the Conseil National des Universités (Section 26) and teaching responsibilities such as courses on Geometry and Shape Spaces and Probability Theory . His work spans from theoretical frameworks (e.g., Hamiltonian modeling of shape evolution) to practical applications like 3D cell imaging and white matter fiber analysis. Publications emphasize interdisciplinary methods, including diffeomorphic registration, varifold-based image analysis, and stochastic shape evolutions. Current projects explore multi-scale modeling of biological systems and AI-driven medical diagnostics. Key Research Themes: Diffeomorphic mappings, computational vision, and functional shape analysis. Teaching: Courses on geometric modeling and probability at undergraduate and graduate levels. Tools Developed: xIV-LDDMM Toolkit for multi-modal biomedical data analysis.
Ammar Mian is an Associate Professor at Université Savoie Mont Blanc, affiliated with the LISTIC lab and Polytech Annecy-Chambéry. He holds a PhD from CentraleSupélec (2016-2019) and conducted postdoctoral research at Aalto University (2019-2020). His research focuses on statistical signal processing, machine learning, and Riemannian geometry with applications in remote sensing and frugal computations. He leads the Qanat project, an experiment tracking tool for reproducible research. Research interests include covariance-based methods for SAR image analysis, robust detection algorithms for sonar and GPR systems, and optimization on Riemannian manifolds. His work emphasizes reproducibility in ML and efficient computational techniques for resource-constrained environments. Key contributions include real-time SAR time-series change detection, robust classification using second-order deep learning models, and novel methods for handling missing data in EEG signals. His recent articles (2023-2025) explore reproducibility frameworks, GPR-based object classification, and Riemannian geometry applications. No awards listed, but maintains active collaborations through LISTIC and industry partnerships. Advises students via internship programs (e.g., Federated ML energy cost analysis). Lab work involves developing open-source tools like Qanat for experiment management and reproducibility.
Alexandre Ern is a Senior Researcher at CERMICS (École des Ponts ParisTech) and INRIA Paris (SERENA team), where he has contributed since 1995 and 2016, respectively. He holds a professorship at École des Ponts (since 1997) and previously served as Associate Professor at École Polytechnique (2010–2022). Since 2015, he heads the Master's program in Applied Mathematics at École des Ponts. Ern is Co-Editor-in-Chief of the IMA Journal of Numerical Analysis (since 2024) and Associate Editor for multiple top journals including SIAM Journal on Scientific Computing and ESAIM Mathematical Modelling and Numerical Analysis. His research focuses on numerical methods (finite elements, discontinuous Galerkin, hybrid high-order schemes), a posteriori error estimation , and applications in fluid/solid mechanics and environmental flows (hydrology, porous media). He develops structure-preserving discretizations for complex PDEs and explores computational geosciences and wave propagation. Ern's publications emphasize robust error analysis , high-order discretizations , and computational efficiency for elliptic, parabolic, and hyperbolic systems. Recent work explores hybrid high-order methods for wave equations, Maxwell's equations, and interface problems, often leveraging polynomial-degree-robust techniques and unfitted meshes. Scientific Awards: Paul Caseau Prize (2020) Nominee, AMIES Prize (2020) ENPC Best PhD Award (supervision) UPE Best PhD Award (supervision) Frontiers of Science Award, Int. Congress Basic Science (2024) He actively advises PhD students (31+ supervised) and postdocs, with projects funded by industrial partners including CEA, EDF, and Safran. His team collaborates with CERMICS and INRIA's SERENA lab, focusing on computational mechanics, model reduction, and large-scale fracture networks.
Pierrick Lotton serves as a CNRS Research Director at Le Mans University's Institute of Acoustics (LAUM), a joint research unit between CNRS and the university. He leads critical work within LAUM's Transducers team, focusing on fundamental and applied research in electroacoustics and thermoacoustics. His institutional affiliation places him at France's premier acoustics research laboratory, which maintains extensive facilities for acoustic measurements, ultrasonic experimentation, and transducer development across multiple specialized domains including materials science, opto-acoustics, and bioacoustics. Lotton's research program centers on two interconnected pillars: electroacoustics and thermoacoustics. His electroacoustic investigations pioneer advanced modeling, development, and characterization of audio transducers with particular emphasis on nonlinear behaviors in loudspeakers and electric guitar pickups. Simultaneously, his thermoacoustic research explores acoustic refrigeration systems, complex couplings between acoustic and thermal energy fields, and transient nonlinear phenomena. This dual focus enables innovative cross-pollination between audio engineering and thermal physics, driving advancements in both fundamental understanding and practical applications of acoustic energy conversion. Analysis of his 2019-2024 publications reveals a consistent trajectory in transducer physics, particularly MEMS-based piezoelectric speakers, voice coil dynamics in magnetic environments, and digital acoustic projection systems. His work demonstrates exceptional methodological diversity spanning analytical modeling, experimental validation, and educational innovation. Notable contributions include the ASKNOWN project's open-access acoustics courseware and breakthroughs in understanding transducer nonlinearities for both consumer audio and specialized applications like fish sound localization. No major scientific awards were documented in the available institutional materials, though his sustained publication record in high-impact journals and presentations at European Acoustics Association forums indicate significant peer recognition. His collaborative research network spans France, Germany, Italy, and the Czech Republic, reflecting strong international engagement. Lotton's academic supervision activities aren't explicitly detailed, but his educational initiatives like the ASKNOWN project demonstrate commitment to pedagogy. His research is supported through LAUM's institutional framework and collaborative projects including European initiatives and ANR-funded programs. Current work appears concentrated on advancing MEMS transducer technology, refining thermoacoustic cooling systems, and developing next-generation educational resources for acoustics. As a core contributor to LAUM's Transducers team, Lotton operates within one of Europe's leading acoustics laboratories. His current projects align with LAUM's strategic focus on transducer innovation and thermoacoustic applications, positioning him at the forefront of both theoretical acoustics research and practical engineering solutions. The laboratory's comprehensive infrastructure supports his work from fundamental wave propagation studies to applied device development.
Anis Matoussi is a Professor of Applied Mathematics at Le Mans University and serves as the Director of the Institut du Risque et de l'Assurance du Mans. He coordinates the master's program in Actuarial Science and leads multiple research initiatives, including ANR DREAMeS (2021-2025) and ITCA (Groupama, Fondation du Risque). Role: Professor, Applied Mathematics Institution: Le Mans University Research Leadership: Director of Institut du Risque et de l'Assurance, Head of Master Actuarial Science His research focuses on stochastic control, backward stochastic differential equations (BSDEs), and their applications in finance, insurance, and energy systems. He has developed numerical methods for second-order BSDEs and studied stochastic nonlinear PDEs, maximum principles for SPDEs, and extended mean field control models. Recent projects include the application of deep learning to forward utilities via ergodic BSDEs and multivariate risk measures. Matoussi has supervised numerous PhD students, including current advisees Zakaria Bensa (industrial thesis with Natixis) and Lucas Da Silva (co-supervised with Caroline Hillairet). Former students like Achraf Tamtalini (Bank of America) and Jing Zhang (Fudan University) hold prominent positions globally. His work includes collaborations on smart grids, control of electrical systems, and robust utility maximization under uncertainty. Publications span journals in applied mathematics, optimization, probability, and financial mathematics, with recent emphasis on numerical schemes and probabilistic representations.
