جستجوی استاد راهنمای دانشگاهی

Tamy Boubekeur is a Senior Director and Senior Principal Research Scientist at Adobe Research France, leading Adobe Research France and the Computer Graphics Group at Telecom Paris. He is a part-time Professor in Computer Science at École Polytechnique, Institut Polytechnique de Paris. Previously, he held roles including Full Professor at Telecom Paris (on leave since 2019), Chief Scientist at Allegorithmic, and Founder/Director of the Computer Graphics Group at Telecom Paris. His work bridges academia and industry, focusing on 3D computer graphics, geometry processing, and real-time rendering. Education: HDR (2012), PhD (2007), and MSc (2004) in Computer Science from French universities. Professional experience spans roles at INRIA, TU Berlin, and UBC. He has been involved in significant projects like FEMONUM (medical modeling) and 3DLife (European project). Research interests include 3D shape analysis, rendering techniques, GPU programming, and global illumination. His work emphasizes efficient processing of geometric data, with applications in medical imaging, animation, and real-time visualization. Notable contributions include SQEM for shape approximation and pioneering point-based global illumination techniques. Honors include multiple Best Paper Awards at Eurographics, SIGGRAPH, and Shape Modeling International. He has supervised numerous PhD students, many of whom now hold academic and industry roles. Boubekeur has chaired major conferences (e.g., EGSR 2019) and served on program committees for SIGGRAPH, EUROGRAPHICS, and others.

• 3D Computer Graphics
• Computer-Aided Design
• Real-Time Rendering
• +۳ مورد دیگر

Jean-Christophe Olivo-Marin is the Head of the Biological Image Analysis Unit and Director of the Carnot Pasteur Institute for Microbes and Health at the Institut Pasteur in Paris, France. He previously served as Director of the Department of Cell Biology and Infection (2010–2014) and continues to lead impactful research at the intersection of biology, computation, and imaging. His research focuses on bioimage informatics , developing computational methods in Machine learning and deep learning for image analysis Bayesian tracking and optical flow algorithms Statistical modeling of spatial patterns in biological systems Mathematical imaging and computational cell biophysics Digital pathology and cancer microenvironment analysis His work enables rigorous quantitative analysis of complex biological phenomena such as cell motility, host-pathogen interactions, and neural dynamics. His recent publications (2024–2025) reflect a strong trend toward AI integration in bioimaging , with advances in deep learning-based segmentation (e.g., Deep ContourFlow), large-scale image annotation (SAMJ), and frameworks for evaluating neuron tracking. There is also a focus on spatial analysis in disease contexts , particularly in cancer and neurodevelopment, combining deep learning with spatial statistics. He has been awarded research funding for projects including Next-generation Structured Illumination Microscopy (SIM) Machine learning for cancer detection using FFOCT Compressive sensing in biological imaging Statistical analysis of spatial coupling in bioimaging (SODA) Olivo-Marin actively mentors students and postdoctoral researchers and contributes to open science through the development and maintenance of Icy , a widely used open-source bioimage analysis platform. He regularly participates in international conferences such as QBI, ICPR, and NEUBIAS, and leads advanced training courses, including the upcoming Advanced Bioimage Analysis with Artificial Intelligence (AI) course at Institut Pasteur in 2026. He leads a dynamic research unit with PhD students, postdocs, and engineers working on cutting-edge image analysis challenges. The team fosters collaboration across disciplines and institutions, promoting open science and community-driven software development.

• Bioimage Analysis
• Computational Biology
• Machine Learning
• +۱۳ مورد دیگر

Laurent Najman is a Professor of Computer Science at ESIEE Paris, part of Université Gustave Eiffel, within the Laboratoire d'Informatique Gaspard-Monge (LIGM) and the A3SI research team. His work focuses on Mathematical Morphology, Image Processing, and applications in Computer Vision and Medical Imaging. He has authored influential books such as Mathematical Morphology: from Theory to Applications and contributed to advancements in hierarchical segmentation, graph-based methods, and discrete geometry. Key research interests include morphological filtering, watershed algorithms, and topological data analysis. Notable achievements include a top-cited paper on ultrametric watersheds and collaborations in medical imaging simulations, such as myocardial perfusion modeling. He advises students like Camille Couprie, recipient of prestigious awards. Najman's interdisciplinary work bridges theoretical foundations with practical applications in fields like bioinformatics and remote sensing. His affiliations include ESIEE Paris and LIGM, where he leads research initiatives. Activities include organizing conferences on discrete curvature and co-developing tools like the Higra library for hierarchical graph analysis. Najman’s contributions emphasize both algorithmic innovation and their interpretability in AI systems.

• Mathematical Morphology
• Image Processing
• Computer Vision
• +۴ مورد دیگر

Dr. Alain Destexhe serves as Research Director (DRCE) and Deputy Director of the NeuroPSI Institute (UMR9197) at CNRS, University of Paris-Saclay, and CEA Saclay Campus in France. As Editor-in-Chief of the Journal of Computational Neuroscience , he leads one of the premier publications in his field. His research program spans multiple international collaborations, with funding from major agencies including the ANR, EC, MRC, NIH, and HFSP. Destexhe's research lies at the interface between physics (dynamical systems) and neuroscience (electrophysiology), focusing on the stochastic activity of the cerebral cortex and its consequences on integrative properties and neuronal coding. His work explores collective dynamics of neuronal networks including oscillations and chaotic states, along with the development of computational methods for electrophysiology such as conductance extraction and analysis of multiple electrode recordings. His laboratory maintains an extensive website ( neurocompute.cnrs.fr ) featuring publications, simulations, and 3D morphological reconstructions. The recent publications reveal a strong emphasis on multiscale approaches connecting molecular mechanisms to large-scale brain activity, with particular focus on thalamocortical systems, slow-wave sleep dynamics, consciousness signatures, and the development of advanced neural network models. His work spans from single neuron dynamics to whole-brain modeling, demonstrating a consistent commitment to bridging different levels of neural organization. Destexhe actively participates in the organization of international conferences and summer schools, contributing to the training of the next generation of computational neuroscientists. His laboratory website provides extensive educational resources including simulation demos, computer-generated animations, and NEURON programs that reproduce figures from published articles.

• Computational Neuroscience
• Dynamical Systems
• Electrophysiology
• +۵ مورد دیگر

Michel Ménard is a Teacher-Researcher at the University of La Rochelle, affiliated with the Mathematics and Computer Science departments. His research focuses on image and signal processing, particularly in cardiovascular imaging, dynamic texture analysis, and UWB radar applications for through-wall imaging. Key projects: ANR DIAMS, FISC consortium, A.Gaugue project Applications: Cardiovascular imaging, environmental monitoring, mobile application programming Research Interests Ménard's work centers on modeling information ambiguity, imprecision, and uncertainty in image analysis, pattern recognition, and information fusion. He has developed generalized fuzzy coalescence methods, non-parametric Bayesian approaches for trajectory analysis, and variational formulations for image filtering inspired by quantum physics. His team focuses on: Dynamic texture modeling via spatio-temporal decomposition Low-level image processing with information theory Through-wall imaging systems using UWB radar Information fusion techniques with minimal a priori assumptions Applications in coastal environment monitoring and biomedical imaging Publications Ménard's publications reflect his expertise in advanced image processing techniques applied to diverse domains. Notable contributions include: Theoretical works on total variation and sublinear functionals Algorithm developments for multistatic radar systems Applications in 3D bee tracking and cardiovascular flow analysis Extensions of Chambolle's algorithm to color images Decomposition methods for dynamic textures Integration of quantum physics concepts in image filtering Collaborations He collaborates with: Laboratoires: L3i, MIA, CLDG/BQR, IRPHE CNRS, ETIS, LASIE Institutions: University Hospitals of Poitiers and Angers, ONERA, LEAT, Tronico Researchers: Abdallah El-Hamidi, Alain Gaugue, Damien Coisne, Gilles Aubert Teaching Ménard teaches across eight departments/programs including: Electronics and Industrial Computing Automation Network Security and Cryptography Video Game Programming Smartphone Programming Digital Media Distribution He has developed new educational initiatives in mobile application programming since 2010.

• Image Processing and Analysis
• Signal Processing
• Pattern Recognition
• +۷ مورد دیگر

Ivan Šmilauer is a Senior Lecturer in Czech Language and Linguistics at the Institut national des langues et civilisations orientales (Inalco) in Paris. He is affiliated with the PLIDAM research center and serves as co-responsible for axis 5 of PLIDAM focused on "Development and practice of digital tools for language and culture teaching and learning." Previously, he served as vice-president of Inalco and digital delegate (2019-2024). Šmilauer completed his PhD thesis titled "Acquisition du tchèque par les francophones : analyse automatique des erreurs de déclinaison" (Acquisition of Czech by French speakers: automatic analysis of declension errors) under the direction of Patrice Pognan at INALCO and Eva Hajičová at Charles University in Prague. His thesis was defended in Paris on November 29, 2008 with congratulations from the jury. His primary research interests span Czech language and linguistics, natural language processing, teaching Czech as a foreign language, modeling of Czech morphology acquisition, and error analysis. Šmilauer has pioneered the development of digital tools for language learning, particularly focusing on Czech grammar instruction. His work bridges theoretical linguistics with practical applications in language education, emphasizing how computational approaches can enhance language acquisition. Šmilauer's scholarly output demonstrates a consistent focus on the intersection of language technology and pedagogy. His publications reveal evolving trends from theoretical linguistic analysis toward practical applications in digital language learning environments. He has made significant contributions to understanding error patterns in Czech language acquisition, particularly in declension systems, and has translated this research into practical teaching tools. As an educator, Šmilauer teaches Czech grammar courses at various levels (L1-L3) in the LLCER ("Langues, littératures et civilisations étrangères et régionales") program with a Czech specialization, as well as advanced Czech language practice in the Master's program "Langues, cultures et sociétés du monde" with a European-Eurasian track. Šmilauer has developed several important pedagogical resources, most notably the CETLEF platform - a web application providing Czech declension exercises with automatic error diagnosis, available since 2008 with over 800 registered users. He also coordinated the Czech team for the MOOC "Kit de contact en langues" project (2015-2017) and developed the CETLEF-Slovak platform for Slovak declension. He has organized numerous academic events, including co-organizing the "Journées AHFLO'" in 2023, the "BOOTCAMP n°#9" of VPNUM in 2022, and the "Journée de la pédagogie numérique à l'Inalco" (JPNI2020) in 2020. Since 2009, he has co-organized the "Informels linguistiques" seminar at Inalco with Olivier Bondeelle and Nicolas Aubry.

• Czech Language and Linguistics
• Natural Language Processing
• Teaching Czech as a Foreign Language
• +۵ مورد دیگر

Charles Baroud is a Principal Investigator and Researcher at the Institut Pasteur in Paris, France. He leads a multidisciplinary Quantitative Biology Program group integrating microfluidics , mathematical modeling , and biomedical engineering to study biological processes at single-cell resolution. Research Focus: The group develops anchored microfluidic droplet platforms for quantifying antibiotic resistance in monoclonal bacterial populations and analyzing mechanical forces in 3D tumor models . Their work bridges physical sciences with cell biology to address challenges in infectious diseases and cancer. Scientific Contributions: Recent articles highlight probabilistic antibiotic susceptibility curves (2024), APC mutation effects on T cell interactions (2024), and 3D mechanobiology of cell aggregates (2024). The lab actively engages in technology transfer via startup spin-offs and licensing agreements. Laboratory: The BaroudLab combines microfabrication , image analysis , and data science tools. Former members have founded three startup companies and secured faculty positions internationally, demonstrating the lab's impact on both academia and industry.

• Microfluidics
• Quantitative Biology
• Antibiotic Resistance
• +۳ مورد دیگر

Erwin Frey is a Professor of Theoretical Physics at the Faculty of Physics, Ludwig Maximilian University of Munich (LMU), where he leads the Frey Group. His research focuses on the physics of living systems, statistical physics, and emergent phenomena in complex systems. He is particularly known for his interdisciplinary approach connecting theoretical physics with biological processes. His research interests encompass statistical physics, biophysics, and nonequilibrium systems, with specific focus on active matter, self-organization in biology, and the fundamental principles underlying complex biological systems. His work bridges theoretical physics with biological applications, exploring how physical principles govern living systems at various scales. Frey's research group investigates diverse phenomena including protein pattern formation, cell division mechanisms, morphogenesis, and synthetic biology. His work demonstrates how fundamental physical principles can explain complex biological processes, with applications ranging from bacterial cell division to immune system organization. His scientific contributions include significant advances in understanding pattern formation in biological systems, particularly the Min protein system in E. coli and thymic architecture development. His group's work shows how robust spatial organization emerges from simple physical principles in living systems. As an educator, Frey teaches advanced topics in theoretical physics, including his lecture series on 'Nonequilibrium Field Theories and Stochastic Dynamics,' which covers Langevin equations, Fokker-Planck formalism, and path integrals with applications to active matter and soft condensed matter physics. He actively collaborates with experimental groups, including Suckjoon Jun's lab at UCSD, and participates in international research networks and conferences, such as the upcoming conference on 'Emerging Trends in Physics of the Cell' at TUM in October 2025.

• Theoretical Physics
• Statistical Physics
• Biophysics
• +۵ مورد دیگر

Benoît Naegel serves as Full Professor at the University of Strasbourg within the ICube research institute, specifically leading activities in the IMAGeS (Images, Modeling, Learning, Geometry and Statistics) team. His office is located at 300 Bd Sébastien Brant, BP 10413, 67412 Illkirch CEDEX, France. His research spans mathematical morphology with specialization in image segmentation techniques, particularly hierarchical approaches using component-trees and component-graphs. He integrates machine learning methodologies into traditional morphological operations, with strong application focus in medical imaging domains including angiographic cerebral MRI (VIVABRAIN Project), abdominal CT scans, PET/CT multimodal imaging, and electronic microscopy for structural biology. His recent work shows increasing incorporation of deep learning techniques. Professor Naegel teaches across multiple academic levels: Computer Vision and Machine Learning at Master I3D in Computer Science; Image Processing and Mathematical Morphology at Masters OTG, I3D, IRIV, and Healthtech programs; System Programming at L2 Computer Science; and Graph Theory/Image Processing at BUT levels. He maintains active research software development through GitHub repositories including LibTIM (C++ image processing library) and component-graph implementation tools. His research output shows consistent focus on geometric and statistical approaches to image analysis, with recent emphasis on centerline detection methodologies applicable to vascular structures as evidenced by the 2024 PhD proposal supervised with Adrien Krähenbühl. The work demonstrates progression from traditional mathematical morphology toward hybrid approaches incorporating machine learning.

• Mathematical Morphology
• Image Segmentation
• Hierarchical Approaches
• +۱۰ مورد دیگر

Nira Dyn is a Professor of Applied Mathematics at Tel Aviv University's School of Mathematics, where she has established herself as a leading researcher in geometric modeling and approximation theory. Her academic career spans decades of contributions to subdivision methods and computational mathematics, with a consistent focus on both theoretical foundations and practical applications in computer graphics and image processing. Research Interests Professor Dyn's primary research areas include Geometric Modeling , Subdivision methods , and Multivariate approximation theory , with significant contributions to Computer-Aided Geometric Design (CAGD) and Image Compression. Her current work centers on Nonlinear subdivision schemes and the Approximation of set-valued functions , representing cutting-edge extensions of classical approximation theory to handle complex geometric structures and uncertain data. These interests form a cohesive research program that bridges pure mathematical analysis with computational applications, particularly in handling geometric data through innovative subdivision techniques. Publication Trends Analysis of her recent publications reveals a strong emphasis on advancing subdivision methodologies beyond linear frameworks, with increasing focus on nonlinear schemes capable of handling complex geometries and set-valued data. Her work demonstrates consistent progression from foundational subdivision theory toward practical applications in image compression and geometric modeling, with notable contributions to metric-based approximation techniques. The publications showcase interdisciplinary reach spanning mathematics, computer science, and engineering applications, while maintaining rigorous mathematical foundations in approximation theory. Professional Activities While specific advising relationships and grant information aren't detailed in the available materials, Professor Dyn's extensive publication record in top-tier journals indicates active research leadership. Her collaborations span multiple institutions and disciplines, reflecting the interdisciplinary nature of modern geometric modeling research. The absence of explicit laboratory or team information suggests her work may be primarily theoretical or conducted through collaborative networks rather than a dedicated physical research space.

• Geometric Modeling
• Subdivision methods
• Multivariate approximation theory
• +۴ مورد دیگر

Pascal Bruniaux is a Full Professor and Research Supervisor at the École Nationale Supérieure des Arts et Industries Textiles (ENSAIT) in Roubaix, France, where he leads research in textile engineering and human-centered design. His work focuses on the intersection of textile science, digital technologies, and human anatomy, with particular emphasis on creating innovative solutions for garment design and customization. Professor Bruniaux's research spans four major themes: (1) Modeling, simulation and multi-scale perception of textile materials; (2) Modeling of the Human/Clothing/Environment interface; (3) Analysis and classification of typical and atypical human morphologies; and (4) Development of personalized co-creation processes integrating 3D virtual prototyping, human perception, and knowledge. His work bridges the gap between traditional textile manufacturing and cutting-edge digital technologies, with applications ranging from everyday apparel to specialized medical garments and protective clothing. His recent publications demonstrate a strong trend toward integrating artificial intelligence and machine learning with 3D garment design and virtual prototyping. The research spans disciplines including textile engineering, computer science, human factors engineering, and sustainable fashion, with particular emphasis on improving garment fit, comfort, and customization through digital technologies. His work addresses critical challenges in the fashion industry, including reducing waste through virtual prototyping and improving accessibility for people with atypical body morphologies. Professor Bruniaux has received significant recognition for his contributions to the field: 2016 Gratitude Diploma from Gheorghe Asachi Technical University of Iasi for supporting and promoting their interests PEDR Award for PhD students and research supervision, received annually from the French Ministry of National Education since 2021 Throughout his career, Professor Bruniaux has supervised numerous PhD students and led multiple significant research projects funded by various programs including FUI, Erasmus Mundus, and European H2020. His research has been supported by collaborations with institutions across Europe and Asia, demonstrating the international impact of his work. He has also contributed to the development of innovative teaching methods in textile and apparel design, integrating digital tools into the curriculum. As a key member of the GEMTEX laboratory at ENSAIT, Professor Bruniaux leads the Human Centered Design Group, which focuses on developing technologies that place human needs at the center of textile and apparel innovation. The group's work has applications in diverse areas including adaptive clothing for people with physical disabilities, personalized sportswear, and advanced protective garments.

• Textile Engineering
• 3D Garment Simulation
• Human Body Modeling
• +۵ مورد دیگر

David Coeurjolly is a Research Director at the French National Center for Scientific Research (CNRS) affiliated with LIRIS laboratory at Claude Bernard University Lyon 1. He leads the Origami research team and holds several leadership positions including Director of GdR Informatique Géométrique et Graphique and Co-lead of PEPR ICCARE. As co-founder of the DGtal library and General Chair of the Graphics Replicability Stamp Initiative, he significantly influences computational geometry research. His research spans digital geometry, discrete algorithms, Monte Carlo rendering, and geometry processing. Core innovations include work on optimal transport, low-discrepancy sampling, digital surface regularization, and curvature estimation methods. His approaches combine theoretical mathematics with practical implementations for computer graphics and scientific computing applications. Recent publications demonstrate strong focus on: Efficient transport algorithms (BSP-OT, Rectified Flows) Sampling theory innovations (Sobol' sequences, Owen scrambling) Digital geometry foundations (Gauss digitization, Laplace-Beltrami operators) Geometric transformations (bijective rotations, plane probing) Awards include: 🎫 Best Paper Award, SIGGRAPH Asia 2024 🎫 SGP Software Award 2016 He leads multiple ANR grants including SSLAM (point cloud ML), StableProxies (geometry processing), and MoCaMed (medical physics). His lab develops open-source tools like DGtal and maintains active collaborations through international initiatives like the Graphics Replicability Stamp.

• Digital Geometry
• Geometry Processing
• Point Sampling
• +۴ مورد دیگر