جست‌وجوی استاد و پژوهشگر

Chua Tat Sengمشاهده پروفایل

استاد

• unstructured data analytics
• multimedia information retrieval
• recommendation systems
• +۶ مورد دیگر

Chua Tat Seng is a Professor at the School of Computing, National University of Singapore (NUS), holding the KITHCT Chair Professorship since 2009. He serves as co-Director of the NExT++ Center, a joint research center between NUS and Tsinghua University focused on Extreme Search. His academic career spans over three decades at NUS, where he has held various leadership positions including Acting Dean of the School of Computing (1998-2000) and Acting Head of the Department of Information Systems & Computer Science (1996-1998). Professor Chua's research spans unstructured data analytics , multimedia information retrieval , recommendation and conversation systems , and emerging applications in e-commerce and fintech . He established the Lab for Media Search (LMS) at the School of Computing and has been instrumental in advancing multimodal learning and search technologies. His work bridges theoretical foundations with practical applications, particularly in developing trustable AI systems for real-world deployment. His recent publications demonstrate a strong focus on large language models for recommendation systems , multimodal learning , and generative AI applications . The research trends show increasing emphasis on LLM-based recommendation, multimodal understanding, and addressing fundamental challenges in AI reliability, fairness, and efficiency. His work spans theoretical advancements in representation learning to practical applications in e-commerce, finance, and healthcare domains. ACM SIGMM Technical Achievement Award 2015 Multiple Best Paper Awards across ACM Multimedia, IEEE Transactions, and MMM conferences (2007-2020) Professor Chua has supervised 37 PhD students since 2004, establishing himself as a dedicated mentor in the academic community. His research has been supported by substantial grants including NExT++ ($12 million), Base Metals Price Forecasting ($200,000), and Multilingual Multimodal Knowledge Graph ($500,000). He maintains active collaborations with Tsinghua University, University of Southampton, and industry partners like Four Elements Capital and Singapore Press Holdings. As co-Director of the NExT++ Center, he leads a major research initiative focused on Web Intelligence and User Empowerment. His visiting professorships at Tsinghua University (2017-present) and Zhejiang University (2021-present) reflect his international impact in the field of multimedia and AI research.

Yuki M. Asanoمشاهده پروفایل

استاد

• Artificial Intelligence
• Machine Learning
• Computer Vision
• +۶ مورد دیگر

Yuki M. Asano is a full Professor at the University of Technology Nuremberg , leading the Fundamental AI (FunAI) Lab . Previously, he led the QUVA Lab at the University of Amsterdam and earned his PhD at the Visual Geometry Group (VGG) of the University of Oxford under Andrea Vedaldi and Christian Rupprecht. University of Technology Nuremberg (2024–present) University of Amsterdam (prior to 2024) University of Oxford (PhD, 2020) His research spans Artificial Intelligence , Machine Learning , and Computer Vision , with a focus on Causal Representation Learning , Self-Supervised Learning , and Efficient Model Adaptation . He pioneered techniques like BISCUIT (causal variable identification) and VeRA (parameter-efficient fine-tuning). His work extends to Medical Imaging and Environmental Monitoring through applications in fetal ultrasound analysis and marine debris detection. Recent publications (2023–2025) highlight advancements in Self-Supervised Learning , Vision-Language Models , and 3D Understanding . Notable papers include TWIST & SCOUT (multimodal LLM grounding), SIGMA (masked video modeling), and GeneralAD (anomaly detection). His ICCV 2023 work on Self-Ordering Point Clouds and MoSiC (optimal-transport motion trajectories) underscores his interdisciplinary approach. He received the JUPITER compute grant (2025) and an Outstanding Paper Award at ICLR 2024 . His collaborations span institutions like MIT-IBM Watson AI Lab, Qualcomm AI Research, and University of Amsterdam.

• Optimization
• Complex Networks
• Statistical Inference
• +۳ مورد دیگر

Stefano NASINI is an Associate Professor at the University of Lille 3, specializing in Quantitative Methods within the Economics and Mathematics Sciences. He holds a HDR (Habilitation à Diriger des Recherches) from the University of Lille 3 (2021), a Ph.D. in Statistics and Operations Research from the Polytechnic University of Catalonia (2015), and a Master in Statistics (2011). His research focuses on optimization, complex networks, statistical inference, and microeconomic applications. He has held academic positions including a post-doctoral role at IESE Business School (2014–2016) and a visiting researcher role at the University of Lisbon (2014). His work spans scheduling optimization, network analysis, financial contagion modeling, and energy system planning. Key contributions include specialized algorithms for large-scale optimization problems and frameworks for decentralized portfolio management. He is a member of the LEM research group and teaches courses in optimization, econometrics, and social network analysis at the Grande École and MSc levels. Publications highlight interdisciplinary applications, including network-based diffusion models, multi-market financial strategies, and dynamic choice analysis. His research bridges theoretical advancements in operations research with practical challenges in economics, energy, and transportation systems. No scientific awards are explicitly listed in the provided materials. His advising roles and grants are not detailed here, but his extensive publication record reflects active collaboration within academic and applied domains.

Anne BOUTINمشاهده پروفایل

استاد

• Thermodynamics
• Molecular Simulation
• Porous Materials
• +۶ مورد دیگر

Anne BOUTIN is a Research Director at the French National Center for Scientific Research (CNRS) and Professor at the École Normale Supérieure (ENS) in Paris, France. She leads the Department of Chemistry at ENS, focusing on the thermodynamics of confined fluids and molecular simulations of porous materials like metal-organic frameworks (MIL-53, ZIF-8) and zeolites. Education: Habilitation (1999), PhD in Chemical Physics (1992), Graduate of École Normale Supérieure (1992), MSc (1990) – all from University of Paris XI, Orsay. Positions: CNRS Research Fellow (1994–2009, University of Paris XI; 2009–present, ENS), Visiting Scientist at UC Santa Barbara (1999), Postdoctoral at Imperial College London (1993–1994). Research spans thermodynamic modeling of adsorption-induced structural transitions, polarizable force fields for charged materials, fluid dynamics in nanopores, and stability analysis of flexible frameworks. Google Scholar highlights recent work on electrolyte intrusion (2023) and defect impacts in zeolites (2023). Publications emphasize computational approaches to water confinement , gas separation , and material flexibility . Her 41+ peer-reviewed articles reflect expertise in Monte Carlo , molecular dynamics , and force field development . Awards: Nathalie Demassieux PhD Award (1993) CNRS Bronze Medal (1999) Legion of Honor (2017) Teaching: Statistical thermodynamics. Students: Supervised 17 PhD/postdoc directions.

Freddy Bouchetمشاهده پروفایل

پژوهشگر

• Statistical Physics
• Climate Dynamics
• Turbulence
• +۵ مورد دیگر

Freddy Bouchet is a Directeur de Recherche at CNRS and a Professeur attaché at École Normale Supérieure de Paris (ENS-PSL). His work bridges mathematical physics, climate science, data science, and statistical mechanics , focusing on turbulent flows, climate extremes, and large deviation theory . He will lead the Laboratoire de Météorologie Dynamique (LMD) starting 2025. Research Themes : Statistical mechanics of geophysical flows (Jupiter's jets, ocean currents). Large deviation theory for rare events in turbulence and climate. Non-equilibrium phase transitions in atmospheric/oceanic systems. Ensemble inequivalence in systems with long-range interactions. Scientific Awards : Three Physicists Prize Collaborations : Tapio Schneider, Antoine Venaille, J. Laurie, O. Zaboronski, B. Dubrulle, A. Venaille. Labs & Teams : Climate and Statistical Mechanics group at ENS de Lyon Future director of Laboratoire de Météorologie Dynamique (LMD/IPSL) Publications span climate dynamics, turbulence, statistical mechanics, and large deviation theory , with applications to Jupiter's atmosphere, ocean vortices, and non-equilibrium systems . His work often challenges paradigms like Tsallis non-extensive statistics.

Xavier Brussetمشاهده پروفایل

استاد

• Supply Chain Management
• Logistics
• Operations Management
• +۶ مورد دیگر

Xavier Brusset is a Professor in Supply Chain at SKEMA Business School since 2016, where he also serves as Director of the PRISM Research Center since 2017. Previously, he held professorial positions at Toulouse Business School (2015-2016) and ESSCA School of Management (2009-2015), where he was responsible for the Master 2 in Purchasing and Supply Chain Management program. His academic journey includes a PhD in Management Sciences from Université Catholique de Louvain (2010) and a Habilitation à Diriger des Recherches from Université Paris Ouest Nanterre La Défense (2016). His research spans multiple critical areas in supply chain management, with particular focus on supply chain resilience, blockchain applications, weather risk management, and pandemic impacts on supply chains. Brusset has developed innovative approaches to understanding how supply chain partners interact, how information affects their behavior, and how external disruptions like weather anomalies and pandemics impact operational efficiency. His work bridges theoretical models with practical applications, often developing decision-support tools for managers facing complex supply chain challenges. Brusset's publication record shows a clear evolution of research interests, beginning with foundational work on supply chain contracts and information sharing, then expanding to weather risk management, and most recently focusing on pandemic disruptions and blockchain applications. His 15 most recent publications (2018-2025) demonstrate increasing sophistication in modeling complex supply chain phenomena, with particular emphasis on network effects, ripple effects, and multi-echelon optimization under disruption scenarios. Editorial board member of Logistics Research Editor of International Journal of Retail and Distribution Management (2022-2023) Recognized EU expert for CINEA research projects evaluation Organizer of the Colloquium on European Research in Retailing (CERR) Reviewer for multiple top journals including International Journal of Production Economics As an advisor, Brusset has supervised doctoral students including R. Alkhudary (co-director, Université Paris 2 Panthéon-Assas) and V. Capocasale (rapporteur). His professional experience extends beyond academia to include industry roles in financial markets and logistics technology, having co-founded WebLogistix, a platform for sharing logistics information in Argentina. His research has practical applications across multiple sectors, particularly in retail, food supply chains, and manufacturing, where he develops tools to help managers mitigate risks and optimize operations under uncertainty.

• Economics of Growth
• Innovation Economics
• Schumpeterian Growth Theory
• +۶ مورد دیگر

Philippe Aghion is a Professor at the College de France holding the chair in Economics of Institutions, Innovation and Growth, and a Professor at INSEAD. He also serves as a visiting professor at the London School of Economics. His academic work has established him as a leading figure in growth economics, particularly through his development of the Schumpeterian Growth paradigm. Professor Aghion's research focuses on the economics of growth, innovation, productivity, and income mobility. He has pioneered the Schumpeterian Growth theory with Peter Howitt, which examines economic growth through the lens of "creative destruction" - where innovation drives progress by replacing outdated technologies and business models. His work analyzes the design of growth policies, the role of competition and industrial policy, the relationship between innovation and inequality, and solutions to the "secular stagnation" observed in developed economies. A recurring theme in his research is understanding how institutions shape innovation and growth dynamics. The analysis of his recent publications reveals a strong focus on innovation economics, environmental sustainability, and the relationship between technological change and economic outcomes. His work spans theoretical developments in growth models and empirical investigations using firm-level data, particularly from France. Key trends include examining how market competition affects innovation, the dynamics of green technology adoption, the impact of globalization on firm behavior, and the relationship between automation and labor markets. His research consistently connects theoretical frameworks with empirical evidence to inform policy design. Professor Aghion has received numerous prestigious awards for his contributions to economics: 2001: Yrjo Jahnsson Award (best European economist under age 45) 2009: John Von Neumann Award March 2020: BBVA "Frontier of Knowledge Award" (shared with Peter Howitt) Fellow of the Econometric Society Fellow of the American Academy of Arts and Sciences As the holder of the Economics of Institutions, Innovation and Growth chair at the College de France (established in 2015), Professor Aghion leads a research team comprising more than twenty researchers. His chair focuses on cutting-edge research examining the economics of innovation, environmental sustainability, productivity dynamics, and household income mobility. His influential books, including "Endogenous Growth Theory" (1998), "The Economics of Growth" (2009), "Competition and Growth" (2006), and "The Power of Creative Destruction" (2021), have shaped the field of growth economics and provided frameworks for understanding modern economic challenges.

• statistical machine learning
• optimization
• sparse methods
• +۵ مورد دیگر

Francis Bach is a Professor and researcher at INRIA, leading the SIERRA project-team since 2011, which is part of the Computer Science Department at Ecole Normale Supérieure (ENS) within PSL Research University. His work bridges CNRS, ENS, and INRIA as a joint research effort. Elected to the French Academy of Sciences in 2020, he currently runs the ERC project SEQUOIA following his previous ERC project SIERRA (2009-2014). His research spans statistical machine learning with focus on optimization, sparse methods, kernel-based learning, neural networks, graphical models, and signal processing. Bach completed his Ph.D. in Computer Science at U.C. Berkeley under Professor Michael Jordan, followed by work at Ecole des Mines de Paris and the WILLOW project-team at INRIA/ENS/CNRS (2007-2010). His recent book "Learning Theory from First Principles" was published by MIT Press in December 2024. Bach's publication record shows consistent high-impact contributions across machine learning theory and applications, with recent work focusing on conformal prediction, diffusion models, optimization theory, and learning theory foundations. His research demonstrates strong connections between theoretical guarantees and practical algorithms, with applications spanning generative modeling, robust optimization, and statistical inference. Elected to French Academy of Sciences (2020) ERC project SIERRA (2009-2014) ERC project SEQUOIA (current) Author of "Learning Theory from First Principles" (MIT Press, 2024) Bach actively mentors numerous PhD students and postdocs, with many alumni now holding faculty positions at institutions like EPFL, Ecole Polytechnique, University of Washington, and University of Montreal. His teaching includes advanced courses on learning theory at ENS's Master's programs. He regularly presents tutorials at major conferences including COLT, NeurIPS, and ICML, demonstrating his leadership in the theoretical machine learning community.

Dond Asha Kisanمشاهده پروفایل

استادیار

• Numerical Analysis
• Computational Mathematics
• Finite Element Methods
• +۴ مورد دیگر

Dond Asha Kisan is an Assistant Professor at the School of Mathematics , Indian Institute of Science Education and Research Thiruvananthapuram (IISER TVM). His research focuses on numerical analysis and computational mathematics , particularly in finite element methods for partial differential equations. He can be contacted at ashadond@iisertvm.ac.in or via phone at +91 (0)471-2778247. PhD : Mathematics, Indian Institute of Technology Bombay M.Sc. : Mathematics, K.T.H.M. College, Nashik Kisan's research spans adaptive finite element methods , stabilized formulations for convection-diffusion problems , and optimal control governed by Stokes equations . His work includes convergence analysis, nonconforming discretizations, and hybrid numerical schemes. Recent publications (2023-2025) address stochastic modeling in liquid crystal physics, advanced WENO schemes, and adaptive algorithms for control problems. Scientific Awards : No explicit awards mentioned in the data, though he held prestigious postdoctoral fellowships including National Post-Doctoral Fellowship and NBHM Post-Doctoral Fellowship. Kisan has extensive teaching experience , including MATLAB workshops and undergraduate course assistantships. He has presented at major international conferences like ICIAM and Hyperbolic Problems, demonstrating global engagement in computational mathematics.

Bruno Palierمشاهده پروفایل

پژوهشگر

• Comparative Politics
• Public Policy
• Social Protection Systems
• +۷ مورد دیگر

Bruno Palier is a CNRS Research Director at Sciences Po, affiliated with the Centre d'études européennes et de politique comparée (CEE) and a key member of the Laboratoire interdisciplinaire d’évaluation des politiques publiques (LIEPP). He is a leading scholar in comparative politics and public policy, focusing on the reform of social protection and pension systems in France and Europe. University: Sciences Po School: Centre d'études européennes et de politique comparée Academic Rank: Researcher (CNRS) His research interests lie at the intersection of political science, sociology, and public policy. He is a foremost expert on the political economy of welfare state reform, social investment strategies, and the dynamics of pension reforms. His work examines how political institutions, economic pressures, and social actors shape the evolution of social policies across advanced democracies. Palier's recent projects center on the contemporary crisis of work in France. He coordinated the 2023 collective work What Do We Know About Work? , which brought together 60 social scientists to document the realities of working conditions, management practices, digitalization, and inequalities. This project has sparked a major public and academic debate, leading to a follow-up initiative, Working Better , which aims to translate research findings into concrete policy proposals for improving the quality of work. Major Works: What do we know about work? (2023) Working Better (2025, forthcoming) The World Politics of Social Investment (2022, 2 vols.) Refonder le système de protection sociale (2014) Réformer les retraites (2021) Throughout his career, Palier has led major research initiatives, including serving as the director of LIEPP (2014-2020) and coordinating the European Network of Excellence RECWOWE. He has also held visiting professorships at Harvard, Tokyo, and Stockholm universities, demonstrating his international academic standing. His work is highly influential in both academic circles and public policy debates, particularly in France. He has a strong record of scientific mediation, actively engaging with the media and policymakers to bridge the gap between academic research and public discourse. His current work on the future of work and social investment represents a significant contribution to understanding and addressing some of the most pressing social challenges of our time.

Thomas Grenierمشاهده پروفایل

دانشیار

• Medical Image Segmentation
• Clustering
• Filtering
• +۳ مورد دیگر

Thomas Grenier is an Associate Professor in the Department of Electrical Engineering at INSA Lyon and a member of the CREATIS laboratory (CNRS UMR 5220, INSERM U1294). He obtained his HDR (Habilitation à Diriger des Recherches) in 2023 and his Ph.D. in Image Processing from INSA Lyon in 2005. His research focuses on medical image segmentation, clustering, and filtering using feature space, scale-space, and deep learning approaches. Doctoral School: EEA (Electronics, Energy, and Automatics) Research Affiliation: CREATIS Lab (CNRS/INSERM/INSA Lyon/Université Lyon 1/Université Jean Monnet Saint-Etienne) He has contributed to 20 papers and co-supervised 5 PhD students, including Léo Dumortier and Florent Guépin. Grenier leads the annual Deep Learning for Medical Imaging (DLMI) school, which he co-founded, and has organized five editions across Lyon and Montreal since 2019. The school emphasizes practical deep learning applications in medical imaging for participants of all expertise levels. His work spans interdisciplinary domains such as medical imaging , deep learning , and image processing , with recent publications on generative AI for MRI synthesis, explainable networks, and segmentation of neurological pathologies in preclinical models. He manages pedagogical platforms, coordinates LabEx PRIMES project activities, and oversees lab room infrastructure for 200 hours/year across 10 training programs. Grenier also leads the MUSIC transversal project on Multiple Sclerosis since 2019.

Joost De Moorمشاهده پروفایل

استادیار

• Environmental Politics
• Social Movements
• Political Participation
• +۴ مورد دیگر

Joost de Moor is an Assistant Professor in Political Science at Sciences Po’s Centre for European Studies and Comparative Politics (CEE) . His research bridges Environmental Politics , Social Movements , and Political Participation , with a focus on climate activism, lifestyle politics, and post-political strategies. He holds a PhD in Social Sciences: Political Science from the University of Antwerp (2016) and has held postdoctoral positions at Keele University (2016-2018) , Stockholm University (2018-2021) , and Leiden University (2021) . A visiting scholar at the University of Mannheim (2015) , his work spans urban environmentalism, climate summit dynamics, and strategic movement adaptation.

• Computer Vision
• Natural Language Processing
• 3D Human Motion Synthesis
• +۳ مورد دیگر

Gül Varol is a permanent researcher at École des Ponts ParisTech's IMAGINE group, an ELLIS Scholar, and Guest Scientist at Max Planck Institute. She holds a PhD from Inria Paris/ENS with awards from ELLIS and AFRIF. Her academic service includes Program Chair at ECCV'24 and Area Chair roles at major conferences. Current affiliations: IMAGINE group (École des Ponts ParisTech), Max Planck Institute Previous roles: Postdoctoral researcher at University of Oxford Her research focuses on vision-language applications, particularly in 3D human motion synthesis, sign language technology, and audio description generation. Key techniques include text-conditioned diffusion models, temporal context modeling, and synthetic data utilization. Scientific contributions recognized through: Google Research Scholar award (2023) ELLIS PhD Award (2020) AFRIF PhD thesis award (2020) Best application paper at ACCV'20 Recent publications demonstrate expertise in: Text-driven 3D motion editing (MotionFix, 2024) Cross-dataset generalization studies (TMR++, 2024) Temporal action composition frameworks (TEACH, 2022) Sign language dense annotation methods (BOBSL, 2022) Zero-shot audio description generation (AutoAD-Zero, 2024) She actively contributes to dataset development including BOBSL (British Sign Language corpus) and SURREACT synthetic action dataset, while pioneering new evaluation metrics for audio description quality and motion retrieval benchmarks.

• Fluid Mechanics
• Hydrodynamics
• Free Surface Flows
• +۴ مورد دیگر

Nicolas Riviere is a Professor at INSA Lyon in the Department of Mechanical Engineering, working within the Laboratory of Fluid Mechanics and Acoustics (LMFA - UMR 5509). He is part of the "Fluides complexes et transferts" (Complex Fluids and Transfers) group and the Environment team. His teaching activities primarily focus on fluid mechanics at the Mechanical Engineering Department of INSA Lyon, covering: General balances (mass, momentum, energy) Aerodynamics Compressible flows Numerical simulation of flows Free surface hydraulics Prof. Riviere's research centers on free surface hydrodynamics, with applications to natural and industrial risks. His work takes an experimental approach, utilizing the laboratory's channel facilities, particularly the channel intersection installation. His research spans river floods with compound beds, urban flooding, sanitation networks, torrential flows, and flow-obstacle interactions. He has developed a strong interdisciplinary focus, co-leading the "Baignades en Rivières Urbaines" studio with Oldrich Navratil from University Lyon 2 and the EVS Laboratory. His publication record demonstrates consistent contributions to the fields of fluid mechanics and environmental hydraulics, with recent work focusing on open-channel flows, urban flooding phenomena, vegetation-flow interactions, and experimental techniques for studying complex hydraulic phenomena. His research often bridges theoretical fluid mechanics with practical environmental applications. Prof. Riviere has received recognition for his work in environmental fluid mechanics, with numerous publications in high-impact journals in hydraulic engineering and fluid mechanics. He has supervised multiple PhD students and research projects related to environmental fluid mechanics and has collaborated with various institutions on interdisciplinary research projects addressing water-related challenges. The laboratory where he works, LMFA, provides extensive experimental facilities including wind tunnels, hydrodynamic channels, and advanced measurement techniques such as PIV (Particle Image Velocimetry), LDV (Laser Doppler Velocimetry), and other state-of-the-art instrumentation for fluid flow analysis.

Chao Liuمشاهده پروفایل

پژوهشگر

• Surgical Robotics
• Teleoperation
• Haptics
• +۲ 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.