جستجوی استاد راهنمای دانشگاهی

Christophe VIGNAT is a Professor at CentraleSupélec, affiliated with the Laboratoire des Signaux et Systèmes (L2S). His research focuses on number theory, special functions, probability, and their applications in signal processing and control systems. He has held visiting professorships at École Polytechnique Fédérale de Lausanne (EPFL) and Tulane University. VIGNAT's work bridges pure mathematics and applied fields, with notable contributions to Bernoulli/Euler polynomials, multiple zeta values, and probabilistic methods in number theory. His recent publications explore topics like partition functions, theta functions, and Ramanujan-type identities. He has delivered talks at international conferences and collaborates widely with researchers in mathematics and physics. Research Interests: Number theory, special functions (Bessel, orthogonal polynomials), probability theory, signal processing, control systems, analytic combinatorics, and their interconnections. His work often employs symbolic computation and probabilistic approaches to uncover identities and structures in mathematical analysis. Publications Trends: Recent articles emphasize partition theory, zeta functions, and integrals related to classical polynomials. His collaborations highlight interdisciplinary efforts between pure mathematics and applied sciences. Over 150 refereed papers and conference contributions demonstrate his prolific output across diverse mathematical domains. Education: While specific academic history isn’t detailed, his roles and publications suggest advanced training in mathematics and engineering, typical for a full professor in systems and control.

• Mathematics
• Number Theory
• Probability Theory
• +۴ مورد دیگر

Eric Collet is a University Professor and Head of Department at the Institute of Physics of Rennes (IPR), a joint research unit of CNRS and Université de Rennes. His work centers on ultrafast photoinduced phase transitions, spin-crossover materials, and the control of functional materials using light and THz excitation. He leads a dynamic research team and is deeply involved in international collaborations, particularly through the IM-LED International Laboratory with Japan. University: University of Rennes School: Institute of Physics of Rennes Department: Department of Materials and Light Academic Rank: Professor Email: eric.collet@univ-rennes.fr Professor Collet's research explores the ultrafast dynamics of molecular and condensed matter systems, especially those exhibiting multistability and photoresponsiveness. His work combines femtosecond optical and X-ray techniques to probe structural and electronic changes at atomic scales. Key areas include spin-crossover phenomena, photomagnetism, ferroelasticity, and nonlinear phononics. He investigates how light can trigger cooperative responses in materials, leading to persistent phase transitions with applications in photonics and memory devices. The recent publications of Eric Collet reveal a strong focus on ultrafast structural dynamics, photoinduced charge and spin transitions, and the coupling of electronic states with lattice distortions. His team frequently employs advanced X-ray methods at large-scale facilities like ESRF and LCLS. The research spans from fundamental quantum dynamics to applied materials science, with recurring themes in symmetry breaking, cooperative switching, and room-temperature photoresponse in molecular systems. Scientific awards and recognitions include: CNRS Silver Medal (2020) Louis Ancel Prize, French Physical Society Hot Paper selection in PCCP (2019) Very Important Paper recognition in Eur. J. Inorg. Chem. (2019) News & Views feature in Nature Chemistry (2020) Eric Collet actively mentors PhD students and postdoctoral researchers, and has supervised numerous publications in top journals. He has led major scientific initiatives such as the UCM2018 symposium and JMC2021 conference. His research is supported by grants from ANR, CNRS, and the Institut Universitaire de France. He collaborates extensively with institutions in France, Japan, and beyond. His research is conducted primarily within the Department of Materials and Light at the Institute of Physics of Rennes. He co-directs the IM-LED International Laboratory with Prof. Shin-ichi Ohkoshi (University of Tokyo) and collaborates with groups in Bordeaux, Lebanon, and Japan. His lab specializes in time-resolved X-ray diffraction, ultrafast spectroscopy, and nonlinear optical control of materials.

• Ultrafast Phenomena
• Photoinduced Phase Transitions
• Spin-Crossover Materials
• +۷ مورد دیگر

Chao Liu is a Research Scientist at CNRS (French National Center for Scientific Research) since 2008, affiliated with the DEXTER team and the Department of Robotics, LIRMM at University of Montpellier, France. He earned his Ph.D. in Electrical & Electronic Engineering from Nanyang Technological University, Singapore (2006). Current research focuses on surgical robotics , haptics , teleoperation , and nonlinear control theory with applications in computer vision. His work addresses challenges in robotic-assisted telesurgery, including: Stable and transparent human-robot interaction through wave variable compensators and passivity filters Physiological motion compensation using spatio-temporal LSTM and dual Kalman filters EMG-based motion recognition for surgical skill assessment 3D soft-tissue reconstruction with stereo-endoscopes and deep learning Dr. Liu leads European and French projects like: TS2RT (CNRS-funded): Safer teleoperation with motion compensation ROBACUS (ANR-funded): Needle positioning with MPC control HaTUMoCo (CNRS-funded): Haptic teleoperation with uncertainty handling ARAKNES (EU-funded): Microrobotic systems for endoluminal surgery Scientific honors include Senior Member of IEEE and Member of Sigma Xi . He supervises Ph.D. and Master's students working on topics such as concentric tube robot optimization, haptic teleoperation, and EMG-based force estimation. Dr. Liu serves on IEEE Technical Committees for Telerobotics and Haptics , and as Technical Editor of IEEE/ASME Transactions on Mechatronics.

• Surgical Robotics
• Teleoperation
• Haptics
• +۲ مورد دیگر

Jean Ponce is a Professor at Ecole Normale Supérieure - PSL and a Global Distinguished Professor at New York University's Courant Institute and Center for Data Science. He serves as Scientific Director of PRAIRIE Interdisciplinary AI Research Institute and co-founded Enhance Lab, commercializing super-resolution imaging software. His research focuses on computer vision, machine learning, robotics, and image processing. Ponce has held roles at Inria, MIT, Stanford, and the University of Illinois, and is an IEEE and ELLIS Fellow. He has served as chair of major conferences like CVPR, ECCV, and ICCV, and authored the textbook 'Computer Vision: A Modern Approach.' Research interests include statistical models for exoplanet detection, neural networks for 3D reconstruction, and self-supervised learning. His work combines theoretical foundations with practical applications in astrophysics, robotics, and imaging. Notable awards include the IEEE CVPR Longuet-Higgins Prize (2016, 2020) and ICML Test-of-Time Award (2019). Key projects include Enhance Lab's high dynamic range imaging and PRAIRIE's interdisciplinary AI initiatives. Ponce's articles explore cutting-edge topics like neural object priors, geodesic motion planning, and satellite image analysis. His contributions bridge academic research and industrial applications, emphasizing both fundamental theory and real-world impact.

• Computer Vision
• Image Processing
• Machine Learning
• +۳ مورد دیگر

Stéphane Doncieux is a University Professor in Computer Science at Sorbonne University, where he is affiliated with the Institute of Intelligent Systems and Robotics (ISIR), a joint research laboratory with CNRS. Since January 2024, he has served as Director of ISIR, following a term as Deputy Director from 2019 to 2023. He leads the ASIMOV research team and is based at the Pierre and Marie Curie Campus in Paris. His primary research interests lie in cognitive and developmental robotics, with a strong focus on open-ended learning, evolutionary algorithms, and adaptive systems. He investigates how robots can autonomously learn diverse skills through mechanisms such as novelty search, quality-diversity optimization, and intrinsic motivation. His work bridges theoretical foundations in artificial life and practical applications in robotic manipulation, perception, and control. The recent publications highlight a consistent trend in advancing robotic learning under sparse rewards and in open-ended environments. Key themes include quality-diversity optimization for grasping, state representation learning, sim-to-real transfer, and the development of behavioral repertoires. These works are published in high-impact journals such as IEEE Transactions on Robotics, Evolutionary Computation, and Frontiers in Robotics and AI. Coordinator, DREAM FET H2020 project (2015–2018) Principal Investigator, ANR projects on Creative Adaptation by Evolution, Learning Movement Skills, and Grasping with Multimodal Feedback Involved in European initiatives including VeriDREAM and HumanE-AI-Net He has supervised numerous PhD and Master’s students, including Leni Le Goff, Giuseppe Paolo, Alban Laflaquière, and Achkan Salehi, often in collaboration with leading researchers like Olivier Sigaud and Jean-Baptiste Mouret. He teaches computer science and robotics at both undergraduate and graduate levels at Sorbonne University. Doncieux has been instrumental in shaping research directions in evolutionary and developmental robotics, notably through his leadership in the IEEE Task Force on Evo-Devo-Robotics and his editorial contributions. His lab, ASIMOV, fosters interdisciplinary research integrating computer science, neuroscience, and engineering to create more autonomous and intelligent robotic systems.

• Cognitive Robotics
• Developmental Robotics
• Evolutionary Robotics
• +۱۶ مورد دیگر

Francesco Fanelli is a Research Professor at the Basque Center for Applied Mathematics (BCAM) under Ikerbasque - Basque Foundation for Science. He is on leave from Université Claude Bernard Lyon 1 and Institut Camille Jordan since September 2023. His work spans partial differential equations (PDEs), fluid dynamics, harmonic analysis, and asymptotic behavior of non-homogeneous fluids. He has made significant contributions to: Hydrodynamics of inviscid and compressible fluids Multi-scale analysis and singular perturbation problems Well-posedness theory for hyperbolic operators with low regularity coefficients Fourier analysis methods in PDEs (Littlewood-Paley theory, paradifferential calculus) His research intersects with geophysical fluid dynamics, magnetohydrodynamics (MHD), and turbulence theory. His 15 most recent publications focus on: Ekman boundary layers and pumping effects Kolmogorov turbulence models Fast rotation asymptotics Low Mach number limits with stratification Singular integrals and Besov space applications Scientific recognition includes: PEDR teaching and research excellence fellowship (2017-2020, renewed 2021-2025) ERC Consolidator Grant finalist (2024) Vinci 2010 fellowship He organizes and participates in international conferences on fluid dynamics and PDEs. Collaborators include leading researchers from institutions in France, Italy, Spain, Poland, and Chile.

• Partial Differential Equations
• Fluid Dynamics
• Harmonic Analysis
• +۶ مورد دیگر

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.

• Computational Statistics
• Machine Learning
• Monte Carlo Methods
• +۴ مورد دیگر

Philippe Souères is a Researcher at LAAS-CNRS (Laboratory for Analysis and Architecture of Systems) within the University of Toulouse. He leads the Gepetto team, focusing on advanced robotics, humanoid motion generation, and the integration of human biomechanics into robotic systems. His work bridges robotics, neuroscience, and biomechanics, emphasizing optimal control, sensor-based systems, and human-robot interaction. Research interests include robot control (optimal control, nonlinear systems), neurosciences (human motor control, sensorimotor integration), and biomechanics (organization of human movement). Notable contributions include models for humanoid locomotion, human-like motion generation using inverse dynamics, and studies on task-dependent balance in humans and robots. Souères has authored/co-authored over 50 publications, including award-winning work on human movement modeling for robotics. He has supervised numerous PhD students and contributed to projects like the EAR initiative (Robot Audition) and the development of the Pyrène humanoid robot. His research also extends to aerial robotics, ducted fan vehicles, and interdisciplinary collaborations with neuroscientists and biomechanics experts. Awards include the Best Conference Paper Award (2010) for integrating human movement invariants into humanoid robotics. Souères is actively involved in academic outreach, appearing in media discussions on robotics ethics and technological innovation.

• Robotics
• Neurosciences
• Biomechanics
• +۴ مورد دیگر

Rachid Malti is a Professor in the Automatic Control research group at the University of Bordeaux, France, specifically working within the CRONE team at IMS (Laboratoire de l'intégration, du matériau au système). His academic career spans over two decades with significant contributions to fractional calculus applications in control engineering and system identification. Professor Malti's research focuses on: Development of fractional order system identification methods Stability analysis of fractional and time-delay systems Experimental design for fractional model validation Applications in energy systems, thermal networks, and battery modeling CRONE Toolbox development for fractional differential signal processing His publication record demonstrates consistent theoretical and applied contributions, with recent work expanding into district heating networks, lithium-ion batteries, and climate modeling while maintaining strong theoretical foundations in fractional calculus. Professor Malti frequently collaborates with researchers including Stéphane Victor, Abir Mayoufi, and Patrick Lanusse across international boundaries. Professor Malti has published extensively in top-tier journals including Automatica, Communications in Nonlinear Science and Numerical Simulation, and Fractional Calculus and Applied Analysis, establishing himself as a leading researcher in fractional order control systems.

• Control Theory
• Fractional Calculus
• System Identification
• +۳ مورد دیگر

Olivier ALLIX is a Professor at the Laboratoire de Mécanique et Technologie (LMT) at École Normale Supérieure de Cachan (ENS-Cachan). His research focuses on computational mechanics, including multiscale modeling of composite materials, structural failure analysis, and non-intrusive coupling strategies. He has held leadership roles such as Head of LMT-Cachan and Vice-president of the International Association for Computational Mechanics (IACM). Expertise: Computational structural mechanics, material failure, inverse problems, and multiscale approaches. Editorial Roles: Associate editor of multiple journals including Computational Mechanics and Computer Methods in Applied Mechanics and Engineering . Awards: IACM Fellow, Euromech Fellow, and recipient of the Gay-Lussac Humboldt Prize (2019). His work integrates experimental mechanics with computational methods, emphasizing big data applications and model validation. He has organized major conferences like the World Congress on Computational Mechanics and co-led international research initiatives such as the IRTG ‘Virtual Material and Structures’ with Hannover University. Teaching includes advanced courses on structural dynamics, composite materials, and computational mechanics at the Master’s level. His research group collaborates with industries like Safran, IFPEN, and DGA on projects involving fatigue analysis, mooring systems, and composite testing.

• Computational Mechanics
• Structural Mechanics
• Multiscale Modeling
• +۷ مورد دیگر

Elena Panteley is a Research Director at the CNRS and a member of the Laboratoire des Signaux et Systèmes (L2S) at CentraleSupélec. She holds a PhD in Applied Mathematics from Saint Petersburg State University (1997) and has extensive experience in research, including roles at the Institute of Problems in Mechanical Engineering, Russian Academy of Sciences (1986–1998). She co-chairs the International Graduate School of Control at the European Embedded Control Institute (EECI-IGSC) and serves as a Book-reviews Editor for Automatica and Associate Editor for IEEE Control Systems Letters . Education: PhD in Applied Mathematics, Saint Petersburg State University, 1997 MSc/BSc in relevant fields (implied by career progression) Research Interests: Focuses on stability and control of nonlinear dynamical systems, networked systems, multi-agent systems, and their applications. Her work emphasizes robust control, consensus algorithms, synchronization, and distributed control strategies for autonomous systems. She explores theoretical frameworks like Lyapunov methods and adaptive control, with practical applications in robotics and communication networks. Publications: Over 100 peer-reviewed articles in top journals like IEEE Transactions on Automatic Control and Automatica . Recent trends include advancements in consensus algorithms for multi-agent systems, synchronization of nonlinear oscillators, and control under communication delays. Awards: No specific awards mentioned, but contributions to control theory and networked systems are widely recognized. Grants/Advising: Leads research on adaptive control, network synchronization, and robotics. Collaborates internationally and advises on projects involving autonomous vehicles and distributed systems. Labs/Teams: Active in L2S and affiliated with CNRS, contributing to teams like MODESTY, COMEDY, and SYCOMORE. Engaged in transverse research on energy, industry automation, and healthy systems.

• Nonlinear Control Systems
• Networked Systems
• Multi-Agent Systems
• +۵ مورد دیگر

Inbar Fijalkow is a Full Professor at the National School of Electronics and Computer Science (ENSEA) within CY Cergy Paris University. She is a member of the ETIS Research Unit (UMR 8051), focusing on signal processing for wireless communications, optimization, and machine learning applications. Her research bridges theoretical advancements with practical implementation in emerging communication systems. Education & Career: PhD in Signal Processing from TelecomParisTech (1993) Postdoctoral Fellow at Cornell University (1994–1995) Professor at ENSEA since 1999 Former Head of ETIS Research Unit (2004–2013) Research Interests: Signal processing for wireless communications Optimization techniques in massive MIMO and NOMA systems Machine learning applications in communication systems Nonlinear effects mitigation in high-power amplifiers Community & Awards: Member of CoNRS Section 7 (National Committee for Scientific Research) Chevalier de l’Ordre National du Mérite (2015) Founder of the CY Alliance Women in Science Prize (2017) Recent Projects: Active in ANR-funded initiatives (e.g., EcoBioH2, AI4code) and EU projects (e.g., PERSEUS). Her work emphasizes sustainability and AI-driven communication systems. Teaching: Teaches signal processing and wireless communications at ENSEA. Supervises PhD students and master’s theses in communication systems and signal processing.

• Signal Processing
• Wireless Communications
• Optimization
• +۳ مورد دیگر

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

• Materials Science
• Information Technology
• Sensor Technology
• +۵ مورد دیگر

Camilla Fiorini is an Associate Professor at the National Conservatory of Arts and Crafts (CNAM) in Paris, where she conducts research at the Mathematical and Numerical Modeling Laboratory (M2N). She serves as Principal Investigator for the ANR-funded SPARCL project (2025-2029) focusing on structure-preserving reduced order models for conservation laws. Her academic background includes a PhD in Applied Mathematics from the University of Versailles and both MSc/BSc degrees in Mathematical Engineering from Politecnico di Milano. Her research centers on computational fluid dynamics, numerical analysis of PDEs, and sensitivity methods, with specific applications in uncertainty quantification and reduced order modeling. Current projects develop novel approaches for conservation laws that maintain structural properties while improving computational efficiency and reliability. Fiorini's publication record demonstrates consistent focus on sensitivity analysis techniques for complex fluid systems, shock-capturing methods, and uncertainty propagation in hyperbolic PDEs. She received the SMAI-GAMNI PhD Award 2019 (French ECCOMAS Award) for her doctoral dissertation on sensitivity analysis for nonlinear hyperbolic systems. As Principal Investigator of the SPARCL project, she leads a team developing new reduced basis construction techniques for conservation laws. Fiorini actively advises graduate researchers including PhD students Nathalie Nouaime (2021-2024) and Nicolas Lepage (2022-present), plus multiple Master's candidates. Her research group collaborates with institutions including Inria, Sorbonne University, ONERA, and CEA. Current projects include ANR JCJC-funded SPARCL and ANR AHEAD initiatives. She leads the SPARCL research group at M2N laboratory, collaborating with researchers including Alessia Del Grosso, Iraj Mortazavi, and Taraneh Sayadi on reduced order modeling techniques. The team focuses on developing computationally efficient ROMs that preserve physical structures in conservation laws.

• Computational Fluid Dynamics
• Numerical Analysis
• Partial Differential Equations
• +۴ مورد دیگر

Andrea Simonetto is a Research Professor at the Applied Mathematics Unit (UMA) , ENSTA Paris, Institut Polytechnique de Paris. His work spans optimization, control theory, and learning algorithms for large-scale and streaming data , with applications in smart grids, intelligent transportation, personalized health, and quantum computing. Current research focuses on online algorithms for time-varying optimization , personalized optimization for cyber-physical systems , and variational quantum algorithms . Past contributions include theoretical and algorithmic advances in convex/non-convex optimization, distributed optimization (robotic networks, smart grids), and signal processing for sparse reconstructions and parallel computing in particle filtering. Key application domains include renewable energy integration , quantum state preparation , and human-in-the-loop control systems . His research is published in journals like ACM Transactions on Quantum Computing , IEEE Control Systems Letters , and Automatica .

• Optimization
• Control Theory
• Quantum Computing
• +۵ مورد دیگر