جستجوی استاد راهنمای دانشگاهی

Sébastien Tordeuxمشاهده پروفایل

دانشیار

• Numerical Analysis
• Wave Propagation
• Electromagnetic Theory
• +۳ 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.

• Visual studies
• Cinema
• Video
• +۳ مورد دیگر

Martine Beugnet is a Professor of Visual Studies at the University of Paris , with a distinguished academic career spanning institutions like the University of Edinburgh (1999-2012). Her research focuses on Visual studies, Cinema, Video, and Digital Media , particularly analyzing intersections between traditional film and emerging digital formats. Her educational background includes a PhD from the University of Edinburgh (1999) , followed by roles as Lecturer, Reader, and Professor there. She has co-directed Edinburgh's Film Studies program (2000-2012) and Paris' UFR of English Studies (2015-2018), while leading the Arts and Visual Culture research axis with Ariane Hudelet. Beugnet's research explores immersive media , digital adaptation , film philosophy , and gender dynamics in cinema. Her work bridges French film theory with global media practices , emphasizing sensory experiences and political dimensions in visual culture. Recent publications like The Gulliver Effect and Cinema and Its Doubles highlight her focus on screen scale evolution , found footage , and mobile cinema . Collaborations with scholars like Kriss Ravetto and Lily Hibberd further enrich her exploration of ghostly motifs and immersive technologies . Beugnet's career includes significant roles in academic leadership and co-editorship of journals such as Interfaces , reflecting her commitment to interdisciplinary research and cross-institutional collaboration between the University of Paris and King's College London.

Brigitte Pientkaمشاهده پروفایل

استاد

• Type theory
• Programming languages
• Logical frameworks
• +۷ مورد دیگر

Brigitte Pientka is a Full Professor in the School of Computer Science at McGill University, where she leads the Computation and Logic group. She received her PhD from Carnegie Mellon University in 2003, and previously studied at the University of Edinburgh and Technical University of Darmstadt. Her educational background includes: PhD from Carnegie Mellon University (2003) Studies at the University of Edinburgh Studies at Technical University of Darmstadt Dr. Pientka's research focuses on developing theoretical and practical foundations for building and reasoning about reliable, safe software systems. She combines theoretical research on logical foundations of computer science in programming languages and verification with system building. Her work spans logics (classical and non-classical), type theory, theorem proving, logic and functional programming, and logical frameworks. She has made significant contributions to the field of contextual types and mechanized metatheory. Her recent publications demonstrate a strong trend toward modal type theory, contextual types, and session types, with applications to functional programming, verification, and meta-programming. She has made significant contributions to the Beluga system, which explores how to combine functional programming with dependently-typed, higher-order data specified in the logical framework LF. Her work often bridges theoretical foundations with practical implementations for mechanized reasoning. Dr. Pientka has received several notable awards: Humboldt Fellowship Test of Time Award @ PPDP'18 for 'Programming with proofs and explicit contexts' Best student paper award at ICLP'03 She is actively involved in mentoring and academic service, having served as PC Chair for ICFP'24, CPP'23 and CPP'24, and as General Chair for POPL'20. She is an Executive Editor of Logical Methods in Computer Science and serves on the editorial boards of the Journal of Functional Programming and ACM Transactions of Computational Logic. She leads the Computation and Logic group at McGill University, which focuses on developing theoretical and practical foundations for reliable software systems through research in logical frameworks, type theory, and programming language design.

• Natural Language Processing
• Computational Linguistics
• Artificial Intelligence
• +۵ مورد دیگر

Marie Candito is a Lecturer at the School of Linguistics, Paris Cité University. She serves as Deputy Director of the Laboratoire de Linguistique Formelle (LLF, CNRS) since January 2025 and Head of the M2 Computational Linguistics program at Paris Cité University. Her research focuses on natural language processing, computational linguistics, and linguistic abilities of large language models. Current Projects : Co-PI of ANR SELEXINI (2021-2025) and scientific coordinator for LLF in ANR PANTAGRUEL (2023-2025) Past Projects : PI of ANR ASFALDA-French FrameNet (2013-2016), scientific coordinator for ANR PARSEME-FR (2015-2019), and member of ANR SEQUOIA (2010-2013) Her work involves measuring and mitigating biases in language models, inducing semantic lexicons from corpora, and studying human vs. LLM word associations. She supervises PhD students including Maria Andueza Rodriguez, Anna Mosolova, and David Kletz.

Jean Auriolمشاهده پروفایل

پژوهشگر

• PDEs
• Control Theory
• Robustness
• +۲ مورد دیگر

Jean Auriol is a researcher affiliated with the Signals and Systems Laboratory , focusing on advanced control theory and partial differential equations (PDEs). His work spans robustness, hyperbolic systems, and infinite-dimensional systems, often addressing real-world applications in engineering and physics. Research Interests: PDEs and Control Theory Robustness in Dynamical Systems Hyperbolic Systems and Networked Control Stochastic and Delayed Systems Recent Publications: Stability analysis of triangular hyperbolic systems Smart traffic management for autonomous vehicles Stochastic hyperbolic PDE stabilization Minimum time control of coupled PDEs Neural network-based parameter estimation for drilling systems

Elise MARESCAUXمشاهده پروفایل

استاد

• Human Resource Management (HRM)
• Talent Management
• Idiosyncratic Deals (i-deals)
• +۸ مورد دیگر

Elise MARESCAUX is a Full Professor and Dean for Faculty at IÉSEG School of Management in France, specializing in Human Resource Management (HRM). She holds a Ph.D. and Master's in Business Economics from KU Leuven. Her research focuses on HR differentiation, idiosyncratic deals (i-deals), talent management, and organizational behavior. She has held leadership roles, including Head of the Department of 'People, Organizations and Negotiation' and Track Coordinator for Human Resource Management. Her work bridges HR practices with employee outcomes, emphasizing developmental HRM, leadership, and work-family dynamics. Education: Ph.D., Business Economics, KU Leuven (2013) Master of Science, Business Economics, KU Leuven (2008) Bachelor in Business Economics, KU Leuven (2007) Research Interests: Elise’s work explores how HR practices impact employee well-being, performance, and organizational outcomes. Key themes include: Idiosyncratic deals and their effects on co-workers and employees Talent management strategies and their ethical implications Developmental HRM practices and leadership roles Work-family balance and organizational culture High performance work practices and innovation Publications & Awards: Her research has been recognized with the 2014 Emerald/EFMD Outstanding Doctoral Research Award and the 2008 Acerta Best Paper Award. Recent articles examine i-deals, elite workforce dynamics, and cross-cultural leadership, reflecting her focus on practical HR challenges. Teaching & Leadership: Elise teaches courses on HRM, talent management, and research methodology. As Dean, she oversees faculty development and academic programs. She co-authored chapters on talent management in Routledge’s companion series and contributed to theoretical frameworks in HR differentiation. Labs & Teams: Her work often involves interdisciplinary collaborations, particularly with colleagues at KU Leuven and IÉSEG, focusing on organizational behavior and HRM systems.

• Numerical Analysis
• Partial Differential Equations (PDEs)
• Finite Element Methods
• +۳ مورد دیگر

Ari Rappaport is a postdoctoral researcher at the Unité de Mathématiques Appliquées (UMA) of ENSTA Paris, part of the Propagation des Ondes, Étude Mathématique et Simulation (POEMS) laboratory. His research focuses on numerical methods for partial differential equations, particularly hybridizable discontinuous Galerkin (HDG) methods for time-harmonic wave propagation and Maxwell equations. He also works on adaptive regularization, error estimation, and high-performance computing implementations. His recent work includes contributions to iterative solvers, finite element methods, and parallel computing strategies. Education and affiliations: Postdoctoral researcher at ENSTA Paris (since 2023?), with involvement in projects like CIEDS ElectroMath (AID/DGA). Collaborates with institutions like Inria and Université de Lille. Research interests emphasize computational electromagnetics, numerical analysis of PDEs, and the development of robust numerical schemes for complex physical models. Key contributions include advancements in HDG methods for Maxwell equations, adaptive error estimation frameworks, and scalable parallel implementations. His work bridges theoretical analysis with practical computational tools for engineering and scientific applications.

Simon Lacoste-Julienمشاهده پروفایل

دانشیار

• Machine Learning
• Optimization
• Deep Learning
• +۵ مورد دیگر

Simon Lacoste-Julien is an Associate Professor at Université de Montréal, affiliated with the Department of Computer Science and Operations Research (DIRO). He also serves as the Associate Scientific Director of Mila – Quebec Institute of Artificial Intelligence and holds the position of Vice President Lab Director at Samsung SAIT AI Lab Montreal (SAIL). His research focuses on machine learning, optimization, and their applications in areas like deep learning, generative models, causality, and computer vision. Lacoste-Julien has held academic positions at INRIA in Paris and has a PhD from UC Berkeley, with postdoctoral work at the University of Cambridge. He teaches advanced graduate courses on probabilistic graphical models and structured prediction. His work includes contributions to optimization algorithms (e.g., Frank-Wolfe methods), causal discovery, and generative models. Lacoste-Julien has supervised numerous students and postdocs, and his awards include being a CIFAR Fellow and Canada CIFAR AI Chair. His research spans theoretical foundations and practical applications, with a strong emphasis on scalable and efficient machine learning techniques.

J. Garrett Morrisمشاهده پروفایل

پژوهشگر

• Programming Languages
• Type Systems
• Functional Programming
• +۴ مورد دیگر

J. Garrett Morris is a researcher and teacher at the University of Iowa's Department of Computer Science, with previous affiliation to the University of Kansas. His work focuses on programming languages, type systems, and formal verification. Active contributor to conferences like POPL, ICFP, and Haskell Recognized for research in session types, linear logic, and functional programming His publications span topics including Exceptional Asynchronous Session Types , Partial Type Constructors , and Constrained Type Families . While no specific awards or students are mentioned in the scraped data, his academic activities include committee roles and keynote sessions.

• Explainable Artificial Intelligence
• Machine Learning
• Data Clustering
• +۴ مورد دیگر

Nicolas Labroche serves as a Researcher in the Department of Computer Science at the Polytechnic School of the University of Tours. He is affiliated with the Fundamental and Applied Computer Science Laboratory of Tours (LIFAT) within the UFR of Sciences and Technology. His academic work spans multiple research domains with significant contributions to machine learning methodology and applications. His primary research focuses on Explainable Artificial Intelligence , particularly for medical applications where model interpretability is critical. He has pioneered methods in clustering of local attributive explanations and discernibility in medical ML models . Additional expertise includes exploratory data analysis through mathematical programming for comparison queries, time series forecasting for environmental monitoring, and preference-based explanations in recommender systems. His work bridges theoretical computer science with practical applications in healthcare, environmental science, and business intelligence. Analysis of his publication trends reveals consistent innovation in making data exploration more efficient and interpretable. Recent work emphasizes user-centric explainability (2024-2025), mathematical optimization for analytics (2022-2023), and synthetic data generation (2022). His research demonstrates strong interdisciplinary connections between computer science, medicine, and environmental science. His laboratory affiliation with LIFAT provides the infrastructure for his computational research. While specific grant details aren't public, his publication record indicates sustained research productivity across multiple European-funded projects focused on data science applications.

Romain Raveauxمشاهده پروفایل

دانشیار

• Image Analysis
• Machine Learning
• Structural Pattern Recognition
• +۵ مورد دیگر

Romain Raveaux is an Associate Professor at the LIFAT Computer Science Laboratory, University of Tours, affiliated with Polytech Tours. His research focuses on Image Analysis, Machine Learning, Structural Pattern Recognition, Graph Matching, Graph Neural Networks, Discrete Optimization, Reinforcement Learning, and Transfer Learning . Email: romain.raveaux@gmail.com , romain.raveaux@laposte.net Address: 64 av. Jean Portalis, Tours, France, 37200 Phone: +33 (0)2 47 36 14 27 Research Interests Graph Matching and Neural Networks Discrete Optimization for Pattern Recognition Transfer Learning in Graph-Based Models Historical Document Analysis Scientific Trends His recent work bridges Graph Neural Networks with Mixed-Integer Programming , focusing on Image Semantic Segmentation and Graph Cycle Detection . Earlier studies emphasize Genetic Algorithms for graph classification and Graph Edit Distance optimization in pattern recognition.

Laurent Pfeifferمشاهده پروفایل

پژوهشگر

• Optimal Control
• Mean Field Games
• Stochastic Optimization
• +۳ مورد دیگر

Laurent Pfeiffer is a researcher at the Signals and Systems Laboratory , focusing on Optimization and Control Theory . His work bridges theoretical advancements in mean field games, stochastic optimization, and numerical methods with practical applications in energy systems and fluid dynamics. Research Interests: Optimal Control, Mean Field Games, Stochastic Optimization, Nonlinear Programming Recent Publications: Explore mean field games, nonconvex optimization, and control theory applications in nuclear energy, gas portfolios, and fluid dynamics. Labs: Signals and Systems Laboratory, specializing in control systems and mathematical modeling.

Didier Theilliolمشاهده پروفایل

استاد

• Fault Tolerant Control
• Control Engineering
• Aerospace Systems
• +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.

• Artificial Intelligence
• Collaborative Robotics
• Human-Machine Interaction
• +۳ مورد دیگر

Madeleine EL ZAHER is a Researcher-Lecturer at CESI, affiliated with the Engineering and Numerical Tools research team. Her work focuses on Artificial Intelligence, Collaborative Robotics, Human-Machine Interaction, and Multi-Agent Systems. She holds a PhD in Computer Sciences from the University of Technology of Belfort-Montbéliard (2013) and a Master’s degree in Computer Sciences and Telecommunications from Paul Sabatier University (2010). Teaching responsibilities include Computer Sciences and Electronics at the Engineering program level, emphasizing project-based learning and training through research. She co-supervises PhD students in industrial robotics and cyber-physical systems, including Abdessalem ACHOUR (defending in 2024) and Badra Souhila GUENDOUZI (defending in 2025). Her research spans semantic mapping in mobile robotics, federated learning for industrial systems, and platooning algorithms for autonomous vehicles. Notable publications include work on semantic mapping with 3D models (2024), federated learning frameworks using genetic algorithms (2023), and verification of platooning systems (2012–2015). No scientific awards are explicitly listed, but her contributions reflect impactful work in autonomous systems and robotics. Grants and lab affiliations are not detailed in the provided text, though her team’s research aligns with CESI’s focus on engineering and numerical tools.

Magnus Madsenمشاهده پروفایل

دانشیار

• Programming Languages
• Compilers
• Type and Effect Systems
• +۷ مورد دیگر

Magnus Madsen is an Associate Professor at Aarhus University, Department of Computer Science. He leads the development of the Flix programming language, a declarative tool integrating logic, functional, and imperative features with Java interoperability. His work spans type and effect systems, program analysis, and JavaScript bug-finding tools, particularly for asynchronous applications. Academic Affiliation: Aarhus University (Denmark) Leadership: Flix Programming Language Magnus's research focuses on programming language design, type systems, and static/dynamic analysis. This includes Datalog constraints, polymorphic effects, and nullability frameworks. His contributions to JavaScript analysis address asynchrony and concurrency challenges. Key trends in his work include declarative program analysis, effect system design, and Datalog-based frameworks like IFDS/IDE. Recent papers explore rank-polymorphic function inference, purity reflection, and stratification in logic programming. Scientific awards include: Sapere Aude grant (2023) Dahl-Nygaard Junior Prize (2022) STEM Grant (2022) Amazon Research Award (2021) DFF Project One (2020) ECOOP 2023 Distinguished Paper ICSE 2016 Distinguished Paper Current PhD students advised: Jonathan Lindegaard Starup, Matthew Lutze, Andreas Stenbæk Larsen (co-advised with Aslan Askarov), Caroline Palma Berger (co-advised with Clemens Nylandsted Klokmose).