جستجوی استاد راهنمای دانشگاهی

Xujia ZHU is an Associate Professor at CentraleSupélec, Paris-Saclay University, affiliated with the Laboratory of Signals and Systems (L2S). His research focuses on uncertainty quantification, surrogate modeling, stochastic simulators, and reliability analysis. He holds an engineer’s degree in Mechanics from École Polytechnique (2015), a Master’s in Computational Mechanics from TU Munich (2017), and a Ph.D. from ETH Zurich (2022). He was a postdoctoral researcher at ETH Zurich until 2023. Education: Ph.D., Chair of Risk, Safety, and Uncertainty Quantification, ETH Zurich, 2022 Master’s (high distinction), Computational Mechanics, Technical University of Munich, 2017 Engineer’s Degree, Mechanics, École Polytechnique, 2015 Research Interests: Xujia’s work bridges numerical simulations and statistics, addressing topics like uncertainty propagation, sensitivity analysis, and surrogate modeling for stochastic systems. Key areas include polynomial chaos expansions, Bayesian active learning, and applications in seismic fragility analysis. Publications: His recent work emphasizes emulation techniques for stochastic simulators, multi-fidelity methodologies, and Bayesian active learning strategies in reliability analysis. Key themes include sparse polynomial chaos expansions and latent variable modeling. Labs/Teams: Affiliated with L2S, he collaborates on transversal projects in energy, industry, and health, leveraging interdisciplinary approaches in uncertainty quantification and computational modeling.

• Uncertainty Quantification
• Surrogate Modeling
• Stochastic Simulators
• +۴ مورد دیگر

Wouter Bos is a Research Director at CNRS working at the Laboratory of Fluid Mechanics and Acoustics (LMFA) at École Centrale de Lyon, France. He leads research within the Turbulence & Instabilities team, focusing on fundamental aspects of fluid dynamics with applications spanning from plasma physics to epidemiology. His academic journey reflects a deep engagement with theoretical and computational fluid mechanics, particularly in turbulence phenomena. Dr. Bos's research interests center on fluid dynamics, with particular emphasis on turbulence in various contexts including two-dimensional flows, magnetohydrodynamics, plasma physics, and statistical mechanics of fluids. His work explores fundamental questions about energy transfer, coherent structures, and statistical properties of turbulent flows. He has made significant contributions to understanding turbulence without vortex stretching, two-dimensional turbulence, and the application of fluid dynamics principles to epidemiological modeling. Analysis of his recent publications reveals a strong focus on theoretical and computational approaches to turbulence. His work spans from fundamental questions about equilibrium states in two-dimensional turbulence to practical applications in plasma confinement and epidemic modeling. The publications demonstrate consistent innovation in turbulence theory, with particular attention to statistical mechanics approaches, spectral analysis, and the development of reduced-order models for complex fluid phenomena. His research shows growing interdisciplinary connections, especially between fluid dynamics and epidemiology as evidenced by his work on modeling the spread of infectious diseases. Dr. Bos actively supervises doctoral students and postdoctoral researchers, with recent students including Tong Wu, Ryo Araki, Smiron Varghese, Wesley Agoua, and Bruce (Xi Yuan) Yin. He participates in collaborative research projects such as the ANR CM2E project (2021-2025) on Characteristic Mapping Method for the Euler Equations, working with researchers from Aix-Marseille University and McGill University. His laboratory work involves both theoretical analysis and computational simulations, with applications ranging from fundamental fluid mechanics to practical problems in energy research (particularly related to ITER and fusion plasma physics) and public health. The interdisciplinary nature of his research demonstrates the broad applicability of fluid dynamics principles across seemingly disparate scientific domains.

• Fluid Dynamics
• Turbulence
• Magnetohydrodynamics
• +۳ مورد دیگر

Kévin Bailly is a Lecturer at Sorbonne University, affiliated with the Institute of Intelligent Systems and Robotics (ISIR) and part of the Machine Learning and Artificial Intelligence (MLIA) team. His research focuses on computer vision, deep learning, and their applications in facial expression recognition, neural network optimization, and medical imaging. Dr. Bailly's research interests span multiple areas including: Computer Vision and Image Analysis Deep Learning and Neural Network Optimization Facial Expression and Action Unit Recognition Model Compression and Quantization Techniques Medical Applications of Artificial Intelligence His recent publications demonstrate a strong focus on neural network optimization, with particular emphasis on quantization, pruning, and compression techniques that maintain model performance while reducing computational requirements. His work spans both theoretical advancements in deep learning and practical applications in healthcare, human-computer interaction, and affective computing. He has developed novel approaches like PowerQuant for non-uniform quantization, RULe for real-time face alignment in degraded conditions, and RED++ for data-free pruning of deep neural networks. Dr. Bailly has published extensively in top-tier venues including ICLR, NeurIPS, IEEE TPAMI, and IEEE TAC, with a consistent output of high-impact research from 2022-2024. His work bridges theoretical computer vision with practical applications, particularly in medical diagnostics and human-computer interaction systems. He actively collaborates with researchers across multiple institutions, including Arnaud Dapogny, Edouard Yvinec, and Matthieu Cord, and has contributed to interdisciplinary projects that apply AI techniques to medical domains such as fracture classification and obstetrics.

• Computer Vision
• Facial Expression Recognition
• Deep Learning
• +۴ 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

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

Sébastien Tordeux is an Associate Professor at the University of Pau, affiliated with the Magique 3D research team in the Faculty of Sciences. His research focuses on numerical methods for wave propagation, particularly Trefftz methods, asymptotic expansions, and electromagnetic/acoustic scattering. He holds a PhD in Applied Mathematics from the University of Versailles Saint-Quentin and has held positions at INSA-Toulouse and ETH Zurich. He has advised multiple PhD students and organized conferences such as the 2017 conference in honor of Abderrahmane Bendali. His work emphasizes high-order numerical modeling and efficient solvers for wave equations in complex media. Education: PhD in Applied Mathematics (2004, Université de Versailles), DEA M2SAP (2001), ENSTA Engineer (1998-2001). Professional roles include Chair of Excellence in Numerical Analysis (INRIA-UPPA 2010-2015), and leadership in Master’s program administration and national academic committees (CNU 26). Research interests span Trefftz methods for time-harmonic models, numerical solvers reducing pollution effects, and asymptotic modeling for small obstacle scattering. Recent contributions include quasi-Trefftz methods for electromagnetic systems and iterative approaches for 3D wave simulations. He has supervised PhD students working on topics like antenna patch models, perforated plate acoustics, and multiscale electromagnetic diffraction. His collaborative projects involve institutions like ONERA and TU Berlin, focusing on high-accuracy wave modeling and computational methods.

• Numerical Analysis
• Wave Propagation
• Electromagnetic Theory
• +۳ مورد دیگر

Anne-Virginie SALSAC is a leading researcher in bioengineering and biomechanics at the University of Technology of Compiègne (UTC), France. She heads the Biomechanics and Bioengineering Laboratory (BMBI, UMR CNRS 7338) and has held an ERC Consolidator Grant (2017) from the European Research Council for her work on multiphysics modeling of microcapsules. Her research focuses on numerical simulation, microfluidics, and bioartificial capsule design for biomedical applications, including hemodynamics in vascular systems and minimally invasive therapies. She has pioneered techniques for microcapsule characterization and sorting, with applications in drug delivery and tissue engineering. SALSAC has collaborated internationally with institutions like Sorbonne Université, University College London, and Queen Mary University of London. Education: Advanced training in bioengineering, with postdoctoral experience in fluid mechanics and biomedical systems. Teaching: Leads graduate courses in mechanical properties of biological materials, microfluidics, and vascular flow modeling at UTC. Previously taught at UC San Diego and University College London. Awards: ERC Consolidator Grant (2017), European scholarship for excellence (2018). Her research integrates experimental and computational methods, emphasizing real-time prediction of capsule deformation and fluid-structure interactions. Key projects include the ERC-funded MultiphysMicroCaps initiative, which explores multiscale modeling of microcapsules under physiological flows. She has developed novel microfluidic tools for capsule sorting and mechanical property analysis, published in top journals like Physical Review E and Journal of Fluids and Structures . SALSAC advocates for scientific mediation, organizing international symposia such as the DynaCaps conference, and has engaged in public outreach via television and media features. Her work bridges fundamental research and clinical applications, with patents on microcapsule fabrication and embolization techniques.

• Bioengineering
• Biomechanics
• Microfluidics
• +۵ مورد دیگر

Denis Duhamel is a Professor and researcher at the Navier Laboratory, affiliated with École des Ponts ParisTech. He teaches mechanics courses at École nationale des ponts et chaussées and previously lectured at École Polytechnique. He earned his doctorate from École des Ponts ParisTech (1994) and research accreditation from University of Marne la Vallée (1998). His research focuses on structural acoustics, railway dynamics, tire-road noise, and numerical modeling of vibrations using Wave Finite Element (WFE) methods. Key areas include railway track dynamics, vibration control, and acoustic barrier performance. Notable projects involve dynamic analysis of periodic structures like railway tracks and metamaterials. Recent publications (2020–2025) emphasize wave-based methods for periodic structures, nonlinear foundation modeling, and in-situ measurements of acoustic barriers. His work bridges theoretical models with practical applications in transportation and structural engineering. Lab affiliations include the Navier Laboratory, a leading center for mechanics and materials research. He collaborates on projects like DEUFRABASE for pavement noise evaluation and ODSurf for optimized road surface design.

• Mechanical Engineering
• Civil Engineering
• Structural Acoustics
• +۴ مورد دیگر

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.

• Electroacoustics
• Thermoacoustics
• Audio Transducers
• +۴ مورد دیگر

Cyril Touzé is a Professor at ENSTA Paris, affiliated with the Fluid Dynamics and Acoustics team within the Mechanics Unit (UME). His research focuses on nonlinear dynamics of mechanical systems, particularly geometric nonlinear vibrations and invariant manifold theory. Expertise in model reduction methods Specializes in wave turbulence transition Develops passive control techniques using nonlinear dampers Applications in acoustic black hole effect and MEMS structures His recent work explores invariant manifold parametrization for nonlinear oscillators, vibro-impact vibration absorbers, and computational methods for geometrically nonlinear systems. He serves as a Topical Associate Editor for Nonlinear Dynamics and collaborates on experimental validations in structural acoustics. Key contributions include: Advanced reduced-order modeling techniques Wave turbulence analysis in thin structures Innovative vibration control strategies Nonlinear coupling mechanisms in musical acoustics Applications to MEMS and aerospace systems

• Nonlinear Dynamics
• Vibrations of Thin Structures
• Model Order Reduction
• +۷ مورد دیگر

Virginie Ehrlacher is a Professor at CERMICS, École des Ponts ParisTech (ENPC), France. She specializes in applied mathematics with a focus on high-dimensional problems, numerical analysis, and computational modeling. Her work bridges quantum chemistry, materials science, and machine learning through innovative mathematical frameworks. Education includes: PhD in Mathematics (2012) from ENPC: Mathematical models in quantum chemistry and uncertainty quantification Habilitation (2020) from Université Paris-Dauphine: Mathematical and numerical analysis of high-dimensional and multiscale problems in materials science Research spans multiscale modeling, tensor decompositions for high-dimensional systems, cross-diffusion equations, and scientific machine learning. Her work frequently addresses challenges in quantum mechanics, materials science, and computational physics using advanced numerical techniques. Publications emphasize: Algorithms for high-dimensional PDEs and eigenvalue problems Model reduction techniques (tensor networks, reduced basis methods) Cross-diffusion systems with biological/physical applications Neural networks for scientific computing Awards and distinctions: Irène Joliot-Curie Prize (2023) Chevalier de l’Ordre National du Mérite (2025) Leadership includes: ERC Starting Grant HighLEAP (2023–2028) ERC Synergy project EMC2 (2020–2026) ANR JCJC project COMODO (2019–2023) She co-leads the EMS Topical Activity Group on Scientific Machine Learning. Affiliated with the CERMICS laboratory, she collaborates on interdisciplinary teams tackling multiscale and data-driven modeling challenges.

• Numerical Analysis
• Applied Mathematics
• Scientific Computing
• +۴ مورد دیگر

Anouar Soufiani is an active researcher specializing in radiative heat transfer, computational fluid dynamics, and plasma physics. His work focuses on complex thermal systems involving coupled radiation-convection phenomena, molecular gas radiation, and high-temperature spectroscopy. Research Interests: Soufiani's investigations span: Fundamental studies of Rayleigh–Bénard convection under radiation effects High-temperature gas radiative properties (CO 2 , argon plasmas) Development of numerical models for turbulent participating media Experimental spectroscopy at extreme temperatures (up to 6000K) Applications in aerospace thermal protection and geological systems Publication Trends: His recent articles (2024-2025) predominantly explore coupled heat transfer mechanisms in confined geometries, with frequent examination of: Radiation-convection interactions in cubical cavities Validation of reduced-order models against experimental data Molecular radiation effects in plasma environments Advanced measurement techniques for radiative properties This consistent focus demonstrates expertise in multiscale thermal transport modeling.

• Radiative Heat Transfer
• Computational Fluid Dynamics
• Plasma Physics
• +۳ مورد دیگر

Didier Theilliol is a Professor of Control Engineering at the University of Lorraine, France, since 2004. He holds a Ph.D. in Control Engineering from Nancy-University (1993). He was awarded the CAS Visiting Professorship by the Chinese Academy of Sciences (CAS) in 2012, during which he collaborated with the Shenyang Institute of Automation (SIA) on flight control and fault-tolerant systems. His research focuses on model-based fault diagnosis (FDI), fault-tolerant control (FTC) for complex systems, and reliability analysis, with applications in aerospace, industrial automation, and robotics. Education: Ph.D. in Control Engineering (Nancy-University, 1993). Research interests include advanced control strategies for linear and nonlinear systems, multi-agent coordination, and safety-critical applications. His work integrates theoretical advancements with practical implementations across industries such as steel production, wastewater treatment, and aerospace. Notable contributions include methodologies for degradation management, distributed observer design, and health-aware control. Recent article trends emphasize fault-tolerant control in multi-agent systems, reinforcement learning for safety-critical tasks, and integration of physics-informed neural networks for system modeling. His publications span topics from model-based diagnostics to real-world applications in UAVs and propulsion systems. Awards: CAS Visiting Professorships for Senior International Scientists (2012). Collaborations include co-working with SIA’s rotorcraft UAV project team and leading European R&D initiatives. He serves as Associate Editor for ISA Transactions and Unmanned Systems , and chairs conferences on fault-tolerant control systems. His research also extends to Bayesian networks for system reliability and particle filter-based prognostics in industrial settings. Labs/Teams: Active in the State Key Laboratory of Robotics (visited during his CAS tenure) and coordinates projects within the German-French Institute for Automation and Robotics.

• Fault Tolerant Control
• Control Engineering
• Aerospace Systems
• +۳ مورد دیگر

Virginie Ehrlacher Galland is a Professor at CERMICS (Centre d'Enseignement et de Recherche en Mathématiques et Calcul Scientifique) within École des Ponts ParisTech. Her expertise lies in applied mathematics, numerical analysis, and computational physics, with a focus on multiscale problems, quantum chemistry, and uncertainty quantification. She holds a PhD from CERMICS (2012) and a Habilitation (2020) from Université Paris-Dauphine. Her research interests include cross-diffusion systems, reduced basis methods, and optimal transport applications. Key contributions involve numerical methods for electronic structure calculations, homogenization techniques, and adaptive algorithms. She leads the ERC Starting Grant HighLEAP (2023-2028) and contributes to major projects like the ERC Synergy project EMC². Awards: Irène Joliot-Curie Prize (2023), Chevalier de l’Ordre National du Mérite (2025). Grants/Projects: ERC Starting Grant HighLEAP (PI), ERC Synergy EMC² (Member), ANR JCJC COMODO (PI). Her work bridges theoretical analysis and computational methods, addressing challenges in materials science, fluid dynamics, and machine learning applications.

• Quantum Chemistry
• Uncertainty Quantification
• Numerical Analysis
• +۵ مورد دیگر

Mohamed Najim is a Professor at IMS Bordeaux (Laboratoire de l'intégration, du matériau au système) affiliated with the University of Bordeaux. He is a member of the Signal and Image Processing research group within the MOTIVE team, where he conducts cutting-edge research in multidimensional signal processing and image analysis. His work spans theoretical developments in signal modeling and practical applications in speech enhancement, image colorization, and communication systems. Professor Najim's research interests focus on advanced signal processing techniques, with particular expertise in autoregressive modeling, Kalman filtering, generative adversarial networks, and multidimensional system analysis. His work bridges theoretical signal processing with practical applications in image processing, speech enhancement, and wireless communications. He has made significant contributions to the development of novel algorithms for texture analysis, channel modeling, and noise reduction in various signal processing contexts. The analysis of his publication record spanning over 25 years reveals a consistent research trajectory focused on fundamental signal processing techniques with expanding applications into modern deep learning approaches. His recent work demonstrates a clear progression from traditional signal processing methods toward integrating machine learning techniques, particularly evident in his 2023 SPDGAN paper which combines manifold learning with generative adversarial networks for image colorization. Throughout his career, Professor Najim has maintained strong theoretical foundations while adapting to emerging technologies in the field. Mohamed Najim has supervised numerous research projects and collaborated extensively with colleagues across institutions. His work shows consistent funding support through participation in various research programs focused on signal processing applications. He has maintained active research collaborations with institutions including CNRS and HESAM University. Professor Najim conducts his research within the IMS laboratory, a leading research center for integration from materials to systems. The laboratory provides state-of-the-art facilities for signal processing research, including specialized computing resources for image processing and speech analysis. His work within the MOTIVE team focuses on developing innovative approaches to complex signal processing challenges across multiple application domains.

• Signal Processing
• Image Processing
• Speech Enhancement
• +۳ مورد دیگر