جست‌وجوی استاد و پژوهشگر

Samuel Herrmannمشاهده پروفایل

استاد

• Stochastic Processes
• Probability Theory
• Applied Mathematics
• +۴ مورد دیگر

Samuel Herrmann is a Professor of Applied Mathematics at the University of Burgundy, France. He is a member of the Statistics, Probability, Optimization and Control team and an external member of the TOSCA project team at INRIA. His research focuses on stochastic processes, particularly asymptotic analysis of non-linear stochastic processes, large deviations, and stochastic resonance phenomena, with applications in climatology, biology, and financial modeling. Education: PhD in Mathematics (2001) - University of Burgundy Habilitation (2009) - Asymptotic analysis related to stochastic processes Research Interests: Stochastic differential equations and their numerical simulation Large deviation phenomena in stochastic processes Self-stabilizing diffusions and stochastic resonance First-passage and exit time problems for diffusions Applications in climatology, biology, and finance Scientific Contributions: Professor Herrmann has published extensively on stochastic processes, with over 50 peer-reviewed articles and a monograph on stochastic resonance. His work includes exact simulation methods for diffusion processes, studies on self-stabilizing systems, and theoretical contributions to large deviations theory. He has collaborated with leading researchers such as Peter Imkeller and David Peithmann. Awards and Recognition: Contributed to the encyclopedia of mathematical physics Co-authored the book "Stochastic Resonance: A Mathematical Approach in the Small Noise Limit" (2014) Teaching and Supervision: He teaches courses on stochastic processes and their simulation at both undergraduate and master's levels, including the Master in Turin program. He has supervised numerous PhD and master's students in stochastic processes and related fields.

• Real-time Systems
• Model Checking
• Critical Systems
• +۴ مورد دیگر

Yasmina Abdeddaïm is an Associate Professor at Université Gustave Eiffel and affiliated with ESIEE Paris. She works within the Laboratoire d'Informatique Gaspard-Monge (Softwares, Networks and Real-time team) and serves as Head of the Master in Artificial Intelligence and Cybersecurity (AIC) program. Her research focuses on real-time systems, critical systems, and scheduling algorithms. University: Université Gustave Eiffel Role: Head of Master AIC program Laboratory: Laboratoire d'Informatique Gaspard-Monge Team: Softwares, Networks and Real-time Her research spans real-time systems , mixed-criticality scheduling , energy-harvesting systems , and probabilistic schedulability . Recent publications analyze compilation optimization impacts on timing variability and propose new models for real-time deep neural networks over GPUs. She employs formal methods like timed automata for scheduling verification. Her teaching includes courses on Real-time Systems , Model Checking , Critical Application Development , and Artificial Intelligence . She is based at Cité Descartes, Champs-sur-Marne, France, with office contact details provided.

Pierre Picardمشاهده پروفایل

استاد

• Insurance Economics
• Risk Management
• Incentive Contracts
• +۴ مورد دیگر

Pierre Picard is a Professor of Economics at École Polytechnique , where he is also a member of the Haut Collège . He holds a PhD in Economics and is a graduate of HEC-Paris. His academic career includes leadership roles such as President of the Risk Theory Society (2005) and President of the European Group of Insurance Economists (EGRIE) (2009). Education: PhD in Economics, HEC-Paris Affiliations: CREST, Risk Theory Society, EGRIE His research focuses on insurance economics , risk management , and contract theory , with applications to catastrophic risks, health insurance, and parametric insurance. Recent publications analyze pandemic business interruption insurance, nuclear liability insurance, and optimal health insurance under ex post moral hazard. Key trends in his work include modeling insurance markets with adverse selection, designing parametric insurance for technology adoption in developing countries, and exploring the role of policy dividends in market equilibrium. He has co-authored multiple papers with A. Louaas, J.-M. Bourgeon, and J. Pinquet. Scientific Awards and Leadership: Junior member, Institut Universitaire de France (1991-1996) President, Risk Theory Society (2005) President, European Group of Insurance Economists (2009) Co-Editor, Annals of Economics and Statistics (past) Co-Editor, Geneva Risk and Insurance Review (past) At École Polytechnique, he teaches courses in Corporate Finance , Microeconomics , and General Insurance at the Master’s level. He also instructs on Topics in Insurance Economics at ENSAE’s Engineering Cycle program.

Irène Marcoviciمشاهده پروفایل

استاد

• Probability Theory
• Dynamical Systems
• Cellular Automata
• +۴ مورد دیگر

Irène Marcovici is a Professor in the Department of Mathematics at the University of Rouen Normandy, affiliated with the Raphaël Salem Mathematics Laboratory (LMRS). She leads the Probability and Dynamical Systems team within LMRS and participates in the ALEA and SDA2 working groups of the GDR Informatique Fondamentale et ses Mathématiques. PhD in Mathematics (2013, University of Paris Diderot) Habilitation à Diriger des Recherches (2021, University of Lorraine) Her research focuses on probability theory , dynamical systems , and cellular automata , with significant contributions to percolation theory, self-organization phenomena, and combinatorics on words. She investigates how randomness influences complex systems, particularly through probabilistic cellular automata and their ergodic properties. Analysis of her recent publications (2021-2025) reveals a strong emphasis on percolation dynamics (e.g., corner percolation with directional bias), self-stabilization mechanisms in cellular systems, and combinatorial structures like Kolakoski sequences. Her work bridges theoretical computer science and pure mathematics, often employing stochastic methods to solve problems in symbolic dynamics and discrete geometry. Supervision & Collaborations: Currently supervising Maxence Poutrel (with Jérôme Casse) Previously supervised Pierrick Siest (2021-2024), Jocelyn Begeot (now Associate Professor), and Pierre-Adrien Tahay (now PRAG at Telecom Nancy) Regular collaborations with Régine Marchand, Nazim Fatès, and Pascal Moyal Laboratory Context: As leader of the Probability and Dynamical Systems team at LMRS, she contributes to France's national research infrastructure in fundamental mathematics, with connections to CNRS and international working groups focused on automata theory and discrete probability.

• Distributed Computing
• Self-stabilizing Algorithms
• Network Algorithms
• +۱ مورد دیگر

Alain Cournier is a University Professor at the University of Picardy Jules Verne (UPJV), France, affiliated with the ALCO research unit (UR 4290) focusing on Algorithmic and Complexity. His office is located in room 401 with contact phone 5913. He maintains an active research profile with continuous publications from 1992 through 2024, primarily in distributed computing and theoretical computer science. Professor Cournier's research centers on fault-tolerant distributed algorithms, specializing in self-stabilizing systems for networked environments. His core contributions span leader election protocols, synchronous unison mechanisms, and message forwarding algorithms in directed and undirected topologies. He pioneered work in snap-stabilization and polynomial-time convergence guarantees, with recent focus on directed network challenges. Earlier career phases included modular graph decomposition algorithms (1990s), while 2018-2019 saw exploration of autoencoder neural networks for anomaly detection in connected buildings. Analysis of his 15 most recent publications reveals strong continuity in distributed algorithms research (12/15 papers), with 2023-2024 works exclusively addressing self-stabilization in directed networks using innovative metaphors like Roman infrastructure. The 2018-2019 neural network studies represent a brief interdisciplinary expansion before returning to core theoretical work. His publications consistently appear in premier venues including PODC, ICDCN, and Theoretical Computer Science, often collaborating with Altisen, Defalque, and Devismes. He operates within the ALCO research unit (UR 4290) at UPJV, which serves as the institutional home for his algorithmic complexity research. This unit facilitates collaboration across the French distributed computing community, evidenced by regular AlgoTel conference participation. While specific lab structures aren't documented, his publication patterns indicate sustained theoretical work with periodic applied explorations in cybersecurity contexts.

Ahmed LOUKILIمشاهده پروفایل

استاد

• Concrete Technology
• Civil Engineering
• Materials Science
• +۵ مورد دیگر

Ahmed LOUKILI is a Professor in the Mechanics, Materials and Civil Engineering Department at Ecole Centrale de Nantes, France. He is affiliated with the Research Institute in Civil and Mechanical Engineering (GeM), where he leads a research team focused on concrete. His work spans concrete technology, structural engineering, and materials science, with a particular emphasis on sustainable construction practices. Professor LOUKILI earned his Bachelor of Civil Engineering from the University of Bordeaux 1 in 1991, followed by a Master of Civil Engineering from Ecole Centrale de Nantes in 1992. He completed his Doctorate Degree (PhD) at Ecole Centrale de Nantes in November 1996 with a thesis on "Delayed deformation of the Ultrahigh-Performance Concrete." In December 2005, he obtained his Habilitation degree from the University of Nantes, enabling him to direct research. His research interests focus on the mix design and mechanical behavior of concrete, durability of cement-based materials, green concrete, and size effects in concrete. Professor LOUKILI has made significant contributions to understanding the early-age behavior of new cementitious materials and the durability mechanics of concrete structures. His work combines experimental approaches with advanced modeling techniques to address critical challenges in concrete technology. Analysis of Professor LOUKILI's recent publications reveals a strong focus on sustainable concrete technologies, including low-carbon cementitious materials, alternative binders like calcined clay and geopolymers, and the application of artificial intelligence for concrete optimization. His research increasingly integrates multi-scale characterization techniques such as nanoindentation and SEM imaging to understand the fundamental mechanisms governing concrete behavior. There's also a growing emphasis on 3D concrete printing and the development of methodologies for eco-design of concrete structures. Professor LOUKILI is a RILEM Senior Member and serves on the TC 195-DTD committee, which develops recommendations for test methods for autogenous deformation and thermal dilation of early-age concrete. He is also a member of the American Concrete Institute (ACI) and regularly reviews for numerous civil engineering journals. Since 2002, he has been a member of the scientific council at Ecole Centrale de Nantes. As Head of the concrete research team in Nantes, Professor LOUKILI has supervised numerous research projects focused on concrete technology and durability. His work has resulted in over 40 refereed papers and book chapters, with recent research expanding into areas like AI applications for concrete optimization and advanced characterization of low-carbon cementitious materials. He teaches courses in concrete technology, reinforced concrete, durability of concrete, and structural engineering. Professor LOUKILI's research is conducted through the Research Institute in Civil and Mechanical Engineering (GeM), where he leads a team investigating fundamental aspects of concrete behavior. His laboratory work combines experimental testing with advanced analytical techniques to address practical challenges in concrete technology and sustainable construction.

Pedro RODRIGUEZ-AYERBEمشاهده پروفایل

استاد

• Model Predictive Control
• Optimization-Based Control Design
• Power Electronics Control
• +۴ مورد دیگر

Pedro RODRIGUEZ-AYERBE is a Professor at CentraleSupélec, University Paris-Saclay, affiliated with the Laboratoire des Signaux et Systèmes (L2S). His expertise spans Model Predictive Control, optimization-based control design, and power electronics control. He holds a Ph.D. (2003) and Habilitation (2014) in Automatic Control from Université Paris-Sud. His research addresses constrained dynamical systems, human-robot interaction, and industrial automation. Education : Ph.D. in Automatic Control (2003), University Paris XI; HDR (2014), Université Paris-Sud. Industry Experience : Fagor Automation (Spain) and Lore (France) from 1996–2000. Research Interests : Focus on robust and constrained control, predictive control algorithms, and applications in robotics, energy systems, and manufacturing. His work bridges theoretical advancements with practical implementations in power electronics and industrial automation. Recent Work : Recent articles explore fragility of control laws, human arm impedance dynamics, and zinc-air battery modeling. His 2025 paper in IEEE Transactions on Automatic Control analyzes polyhedral partition fragility in PWA control systems. Student Supervision : Over 20+ PhD students supervised since 2003, including current advisees in robotics, control systems, and energy engineering. Notable collaborations with institutions like CEA-LIST and CIAMS. Key Projects : Active in interdisciplinary research, including zinc-air battery control (2024), human-robot interaction (2023), and advanced manufacturing precision (2021). His lab contributes to EU industrial and academic initiatives.

• Microelectronics
• Emerging Memories
• Neuromorphic Computing
• +۵ مورد دیگر

Hassen AZIZA is a senior Associate Professor and Head of the Memory Team (MEM) within the IM2NP research unit at Aix-Marseille University, specializing in microelectronics and emerging memory technologies. His work bridges academic research and industrial applications through collaborations with ST-Microelectronics, CEA-Leti, Thales, and international universities. He earned both his Master of Science in Electrical Engineering (MSEE) and PhD with honors from Aix-Marseille University. His educational background established the foundation for his expertise in semiconductor devices and memory systems. His research centers on Microelectronics , Emerging Memories , and Neuromorphic Computing , with specific focus on RRAM reliability, computation-in-memory architectures, and hardware security. Current projects address critical challenges in RRAM variability, fault tolerance, and energy-efficient neural network implementations using memristive crossbars. His work spans from fundamental device physics to system-level integration for IoT and biomedical applications. Analysis of his 15 most recent publications reveals dominant trends in RRAM reliability engineering (35% of articles), neuromorphic hardware implementation (30%), and sensor system development (20%). Key subfields include fault-tolerant memory design, variability-aware neural networks, and low-power IoT circuit optimization, demonstrating consistent focus on bridging device physics with practical system requirements. Best Paper Award at IEEE ETS (2021) for RRAM fault analysis CoolGames Silver Medal (2019) for high-altitude balloon project Eiffel Scholarship for PhD student (2018) Guillemin-Cauer Best Paper Award (2014) Multiple IEEE conference best paper awards (2013, 2011) SIMagine contest finalist/silver medalist (2010, 2009) He has supervised 10 PhD students (8 graduated via industry-oriented CIFRE theses), including Eiffel scholarship recipient Hussein BAZZI. His research is funded through strategic industry partnerships with ST-Microelectronics, CEA-Leti, and Thales Silicon Security, plus European initiatives like the French Tech LAB grant for the SMILE air quality monitoring startup project. Current grants focus on RRAM commercialization and neuromorphic hardware development. As leader of the Memory Team (MEM) within IM2NP's Department of Analysis and Design of Electronic Systems, he directs research on resistive memories, neuromorphic circuits, and sensor interfaces. The team maintains strong industry links through joint projects with semiconductor manufacturers and participates in international standardization efforts for emerging memory technologies.

Patrick Basمشاهده پروفایل

استاد پژوهشی

• Steganography
• Steganalysis
• Digital Watermarking
• +۲ مورد دیگر

Patrick Bas serves as Research Director and Thematic Group Facilitator for the Data Intelligence Group (DatInG) at the University of Lille, France, where he leads the Signal and Images team within the CRISTAL laboratory. His office is located at ESPRIT in Lille's Scientific City, and he holds membership on the institution's Scientific Council. Bas earned his Electrical Engineering degree (1997) and Ph.D. in Signal and Image Processing (2000) from the Institut National Polytechnique de Grenoble. His academic journey includes postdoctoral work at Université Catholique de Louvain, CNRS research at Gipsa-Lab (2001-2009), and a visiting position at Helsinki University of Technology (2005-2008). His primary research centers on steganography, steganalysis, and digital watermarking, with significant contributions to image manipulation detection and neural network applications in multimedia security. He has organized major initiatives including the BOSS steganalysis contest (2010) and served as co-coordinator for the Ecrypt European NoE's watermarking virtual lab (2004-2008). While his Google Scholar profile indicates recent publications in graph theory and combinatorics (2021-2025), these appear inconsistent with his documented research focus on multimedia security as evidenced by his thesis supervision and professional activities. Bas has supervised seven doctoral theses including Rony Abecidan's work on robust image manipulation detection (2024) and Solène Bernard's research on neural network steganography (2021). He has held editorial roles for the Eurasip Journal on Information Security (since 2011) and IEEE Transactions on Information Forensics and Security (2013-2016), and co-organized the International Workshop on Information Hiding (IH07).

• Microbial Ecology
• Synthetic Biology
• Ecological Dynamics
• +۳ مورد دیگر

Daniel AMOR is a Lecturer in the Department of Physics at École Normale Supérieure (ENS), Paris. His research focuses on microbial ecosystems, antibiotic resistance, and synthetic biology, exploring topics like ecological stability, population dynamics, and cooperative growth mechanisms. He contributes to interdisciplinary projects involving experimental microcosms and theoretical models to understand how microbial communities respond to environmental pressures. His work bridges physics and biology, applying concepts from nonlinear dynamics and systems theory to ecological systems. AMOR collaborates with ENS's Physics Laboratory and Kastler Brossel Laboratory, advancing knowledge in synthetic microbial systems and their ecological implications.

Irène Marcoviciمشاهده پروفایل

استاد

• Probability Theory
• Cellular Automata
• Dynamic Systems
• +۳ مورد دیگر

Irène Marcovici is a Professor at the University of Rouen Normandy, affiliated with the Raphaël Salem Mathematics Laboratory (LMRS) and leading the Probability and Dynamic Systems Team. Her research spans probability theory, cellular automata, stochastic processes, and combinatorics, with a focus on ergodicity, percolation, and self-organization phenomena. She collaborates with institutions like the GDR Fundamental Computer Science and its Mathematics and has contributed to journals such as Probability Theory and Related Fields, Annales Henri Lebesgue, and Theoretical Computer Science. Education: Habilitation à Diriger des Recherches (2021, University of Lorraine), PhD in Mathematics (2013, University of Paris Diderot) Research Focus: Marcovici's work explores probabilistic cellular automata, percolation models, and their applications in physics, computer science, and mathematics. Key projects include analyzing stability regions in queueing systems, developing decentralized diagnostics, and studying self-descriptive sequences. Her articles highlight interdisciplinary connections between discrete mathematics and stochastic dynamics. Notable Collaborations: She has co-authored publications with researchers like Jérôme Casse, Régine Marchand, Nazim Fatès, and Mathieu Sablik. Her team participates in the ALEA and SDA2 working groups under GDR Fundamental Computer Science and its Mathematics.

Xavier Claeysمشاهده پروفایل

استاد

• Wave Propagation
• Mathematical Modeling
• Numerical Analysis
• +۵ مورد دیگر

Xavier Claeys is a Professor at ENSTA Paris, affiliated with the Applied Mathematics Unit (UMA) and the Wave Propagation, Mathematical Study and Simulation (POEMS) research team. His work focuses on the mathematical modeling and numerical analysis of wave propagation phenomena with applications in electromagnetics and acoustics. He maintains an active research program with numerous publications spanning from 2007 to the present, demonstrating sustained scholarly contributions to his field. Dr. Claeys earned his PhD from Université Versailles Saint-Quentin-en-Yvelines in 2008 with a thesis on 'Asymptotics and numerical analysis for wave diffraction by thin wires.' He completed his Habilitation from Université Pierre-et-Marie Curie in 2016 with research on 'Boundary integral equations of time harmonic wave scattering at complex structures.' His academic trajectory shows a consistent focus on developing mathematical frameworks for wave propagation problems. His primary research interests center on the modeling and numerical analysis of linear wave propagation phenomena, particularly in the context of frequency domain electromagnetics and acoustics. His specific technical interests include domain decomposition methods, boundary element methods, scientific computing, multi-scale problems, and singularities in elliptic problems. Dr. Claeys has developed specialized software tools including bemtool (a boundary element library) and ddmtool (a domain decomposition library) to support his research, demonstrating his commitment to translating theoretical advances into practical computational tools. Analysis of his publication record reveals a consistent evolution toward increasingly sophisticated domain decomposition approaches, particularly optimized Schwarz methods and multi-trace boundary integral formulations. His work demonstrates a strong theoretical foundation combined with practical implementation considerations, with applications spanning electromagnetic scattering, acoustic wave propagation, and metamaterial analysis. Recent publications show increasing focus on addressing computational challenges related to complex geometries and physical boundaries. Dr. Claeys has led significant research projects including 'NonlocalDD' funded by the French National Research Agency (ANR), which investigated boundary integral equations in conjunction with domain decomposition. He was previously involved in the ANR-funded 'METAMATH' project focused on the modeling and numerical analysis of metamaterials. His research contributes to ENSTA Paris's broader research focus on cutting-edge areas with applications in sustainable energy, transportation, and defense. His work aligns particularly with the 'Waves and Vibrations' research axis at ENSTA Paris, which encompasses activities related to wave propagation phenomena with applications including seismic effects on infrastructure, non-destructive testing, and acoustic management in transportation and energy sectors. Dr. Claeys' theoretical contributions provide foundational support for these applied research directions through advanced mathematical modeling and numerical methods development.

• Distributed Algorithms
• Metric Graph Theory
• Theoretical Computer Science
• +۳ مورد دیگر

Jérémie Chalopin is a Directeur de Recherche (DR CNRS) at LIS (Laboratoire d'Informatique et Systèmes) in Marseille, where he is a member of the DALGO research team. His position at CNRS is affiliated with Aix-Marseille University, one of France's largest multidisciplinary universities. As a senior researcher with habilitation to supervise research (awarded in 2020), he plays a significant role in the French theoretical computer science community. Chalopin's research primarily focuses on distributed algorithms and metric graph theory , with substantial contributions to understanding the theoretical foundations of distributed computing systems and the geometric properties of graphs. His work bridges theoretical computer science with practical applications in mobile agent systems, programmable matter, and network algorithms. He has developed fundamental results in areas including leader election, graph exploration, metric embeddings, and sample compression schemes for graph structures. Analysis of his recent publications reveals a strong trend toward interdisciplinary work combining distributed computing with geometric graph theory. His research on balls in graphs has applications in machine learning, while his work on programmable matter addresses cutting-edge challenges in distributed robotics. The consistent high-quality output in top theoretical venues demonstrates sustained research productivity across multiple subfields. As a habilitated researcher at CNRS, Chalopin supervises PhD students and participates in research projects, though specific details about current students or grants aren't provided in the source material. His long-standing collaboration with Victor Chepoi (appearing in numerous publications) represents a significant research partnership in metric graph theory. Chalopin is based at LIS in the TPR2 building (office 05.28, 5th floor) where he works as part of the DALGO team, which focuses on algorithms and theoretical computer science. His research environment provides strong connections to both the French and international theoretical computer science communities through collaborations with researchers across Europe and beyond.

• Fluid Mechanics
• Turbulence
• Differential Geometry
• +۶ مورد دیگر

RAZAFINDRALANDY Dina is a Teacher-Researcher at the University of La Rochelle, affiliated with the E1 - M2N team. Her research focuses on fluid mechanics, turbulence analysis, and geometric integration methods in applied mathematics. Fluid mechanics and turbulence modeling via symmetry groups Differential geometry applications to partial differential equations Development of time integrators using divergent series resummation Her recent work explores advanced techniques like Lie symmetry groups and discrete exterior calculus to preserve physical properties in numerical simulations. She has contributed to geometric integrators for stiff/non-stiff problems and turbulence model construction. RAZAFINDRALANDY collaborates with researchers such as Aziz Hamdouni and Rama Ayoub, with publications spanning Discrete and Continuous Dynamical Systems , HAL , and conference proceedings. She is actively involved in computational mechanics and numerical physics research.

Antoine Levittمشاهده پروفایل

استادیار

• Quantum Chemistry
• Materials Science
• Numerical Analysis
• +۳ مورد دیگر

Antoine Levitt is an Assistant Professor (CPJ) at the Laboratoire de Mathématiques d'Orsay, Université Paris-Saclay. Previously, he was a researcher at Inria Paris in the MATHERIALS project-team, affiliated with CERMICS at École des Ponts. His research focuses on numerical methods for quantum chemistry and materials science, including density functional theory (DFT), Wannier functions, and electronic structure calculations. He has contributed to theoretical advances in numerical analysis, such as error bounds for DFT and preconditioning techniques for eigenvalue problems. Levitt’s work spans computational physics and applied mathematics, with applications to quantum dynamics, response properties, and defect systems. He has developed open-source software tools like DFTK.jl and Wannierization algorithms . His teaching includes courses on scientific computing, functional analysis, and quantum mechanics at both undergraduate and graduate levels. Key research themes include numerical stability in DFT, analysis of linear response theory, and efficient implementations of conjugate gradient methods. His recent work explores machine learning applications in canonical sampling and mathematical foundations of Density Matrix Embedding Theory.