Christian Rupprecht is an Associate Professor at the Department of Computer Science, University of Oxford, specializing in computer vision and machine learning. His research focuses on unsupervised learning, 3D reconstruction, and visual understanding. His work includes contributions to conferences such as GCPR'25, ICCV'25, and CVPR'25, with papers spanning topics like correspondence estimation, animal pose modeling, and synthetic data generation. He leads projects within the prestigious Visual Geometry Group (VGG). Notably, his paper VGGT received the Best Paper Award at CVPR'25. His research integrates deep learning and geometric modeling, emphasizing robustness and generalization in visual systems. Best Paper Award at CVPR'25
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.
Kiwon Um is a tenured Assistant Professor in the Computer Graphics group at Télécom Paris, France, since October 2019. He focuses on physics-based simulations and data-driven approaches using deep learning, with an emphasis on human visual perception in computer graphics and engineering applications. Education: Ph.D. in Computer Science and Engineering from Korea University His research explores effective simulation of natural phenomena through refined data utilization and develops reliable data acquisition methods for machine learning. He also investigates perceptual evaluation of simulations to advance numerical method understanding. Recent work trends include: (1) turbulence modeling with machine learning integration, (2) elastic material simulation stability, (3) fluid dynamics optimization, and (4) differentiable physics frameworks. His publications range from 2008 to 2025, covering topics like SPH solvers, porous shell simulations, and numerical method validation.
Olivier Sigaud is a Full Professor at Sorbonne University, affiliated with the ISIR (Intelligent Systems and Robotics Institute) and the Machine Learning and Intelligent Autonomous Systems (MLIA) team. He holds an engineering degree from ISEN and dual PhDs in Computer Science (University of Paris XI, 1996) and Philosophy (University of Paris I, 2004). Previously employed at Dassault Aviation (1995–2001), he transitioned to academia as a Lecturer and later a Professor at LIP6 and ISIR. His research focuses on reinforcement learning, robotics, computational neuroscience of decision-making in animals, and human-robot interaction. Key contributions include advances in goal-conditioned reinforcement learning, intrinsically motivated agents, and human-in-the-loop systems. He has co-authored over 100 publications in top-tier conferences (NeurIPS, ICML) and journals, with recent work exploring large language model grounding, open-ended learning frameworks, and motor skill acquisition through interactive curricula. Notable projects include the CURIOUS framework for modular multi-goal RL and the DREAM architecture for open-ended robotic learning. His work bridges theoretical AI with practical robotics applications, emphasizing interdisciplinary collaboration between computer science and neuroscience.
Sophie Lanone is a researcher and team leader of the Genetic-environment Interactions in COPD, Cystic Fibrosis, and Respiratory Pathologies (GEIC2O) team at the Mondor Institute of Biomedical Research (IMRB), affiliated with Université Paris-Est Créteil. Her work focuses on understanding the interplay between genetic and environmental factors in respiratory diseases, particularly COPD, cystic fibrosis, and surfactant-related pathologies. She leads a multidisciplinary team of clinicians and scientists investigating molecular mechanisms, inflammation resolution, and environmental impacts on pulmonary health. Key research themes include the molecular basis of cigarette smoke-induced COPD, genetic and cellular aspects of cystic fibrosis, and the role of specialized pro-resolving mediators in disease. Funding sources include EU programs (e.g., H2020 REMEDIA), ANR, and patient associations like Vaincre la Mucoviscidose. Recent advances include identifying lipid mediator defects in CF patients and demonstrating resolvin E1’s efficacy in correcting ciliary dysfunction. Team members have received awards, such as Khadeeja Adam Sy’s 2024 prize for active participation in CF research. Collaborations span in vitro/ex vivo models, patient cohort studies, and translational approaches toward personalized therapies. The team also explores environmental exposures (e.g., asbestos, nanoparticles) and their long-term respiratory health impacts.
Dr. Yves Boubenec is an Associate Professor at École Normale Supérieure (ENS)-PSL University, Paris, France. He serves as Head of the LSP Neuro Platform and Director of Studies at the Department of Cognitive Studies. Academic Rank: Associate Professor Institution: ENS-PSL Departments: Cognitive Studies (ENS), LSP Neuro Platform Email: yves.boubenec@ens.psl.eu Research Focus: Boubenec investigates neural mechanisms of auditory perception and cognition using integrated methodologies spanning single-neuron electrophysiology to large-scale neuroimaging. His work reveals how context, learning, and multisensory interactions shape sound encoding in mammalian neocortex. Primary Research Themes Context-dependent auditory encoding Perceptual attention mechanisms Task-driven neural plasticity Self-supervised learning models Population-level cortical dynamics Human/ferret auditory comparisons Publication Trends: Recent work (2024-2025) examines speech production networks, premotor auditory categorization, and algebraic structures in sound learning. Earlier studies (2018-2022) focus on population gating, hierarchical auditory coding, and self-voice mechanisms. 2025 Self-voice frequency analysis Hierarchical ferret auditory cortex mapping Temporal window constraints 2024 Premotor category hemodynamics Self-supervised sound structures Human speech cortical encoding Methodological Expertise: Combines awake ferret functional UltraSound, Neuropixels recordings, and computational modeling to analyze neural representations across spatial scales. Specializes in translating animal model findings to human auditory processes.
Marie-Paule Cani is a Professor of Computer Science at École Polytechnique (since May 2017), on leave from Grenoble INP and Inria . She leads the STREAM team at the LIX laboratory (CNRS, École Polytechnique) and collaborates externally with the IMAGINE team at Inria. Her research focuses on advancing intuitive methods for creating 3D shapes and virtual worlds, emphasizing user control and model-based knowledge. Education: 1987: M.Sc. in Computer Science, École Normale Supérieure & University Paris XI 1990: Ph.D. in Computer Graphics, University Paris XI (advisor: Claude Puech) 1995: Habilitation in Computer Science, Institut National Polytechnique de Grenoble Research Interests: Her work spans shape modeling , computer animation , and procedural modeling . She pioneered methods such as implicit surfaces, physically-based animation, and sketch-based interfaces. Recent projects include combining procedural models with intuitive user interactions to streamline 3D content creation. Awards & Recognition: ERC Advanced Grant (2011) for the EXPRESSIVE project 2011 Eurographics Technical Contributions Award 2012 CNRS Silver Medal 2013 Election to Academia Europaea Leadership & Service: She created and led the STREAM (2017–present), IMAGINE (2011–2016), and ÉV@NCE (2003–2010) research teams. She has served as President of Eurographics (2017–present), Technical Paper Chair of SIGGRAPH 2017 , and on editorial boards of ACM Transactions on Graphics , Computer Graphics Forum , and others. Labs & Teams: Active in the LIX laboratory and collaborates with Inria's IMAGINE team. Her work bridges academic research and industrial applications in computer graphics and animation.
Sidonie Christophe is a Senior Researcher (Directrice de Recherche, DR1) at UMR LASTIG, a joint research unit of Université Gustave Eiffel, IGN-ENSG, and EIVP. She serves as co-director of the LASTIG laboratory and leads research in geovisualization, map design, and interactive spatial data exploration. She also holds a part-time advisory role (60%) at the French Ministry of Higher Education and Research in the domain of digital technology, environment, climate, and sustainable urban development. PhD in Geographic Information Sciences Senior Researcher, DR1, MTECT Co-Director, LASTIG Laboratory (since 2021) Former Team Leader, GEOVIS (Geovisualization, Interaction, and Immersion) Advisor, Environment and Urban Climate, French Ministry of Higher Education & Research Her research centers on innovative methods for 2D/3D and nD geospatial data visualization, with a focus on enabling spatio-temporal understanding through visual and non-visual spatial thinking. Her work integrates principles from geographic information science, human-computer interaction, and computer graphics. Key areas include urban climate visualization, tactile and augmented reality for accessibility, expressive cartographic rendering, and cognitive aspects of map design. She investigates how aesthetic and semiotic choices impact map comprehension and utility. The 15 most recent publications reflect a strong trend in interactive and accessible geovisualization, particularly for urban and environmental applications. Topics include neural map style transfer, 3D urban climate analysis, tactile maps for the visually impaired, augmented reality in geography, and visual analytics for crisis and climate data. There is a consistent emphasis on user-centered design, interdisciplinary integration, and the development of tools for decision-making under uncertainty. Scientific Recognition and Service: Invited speaker at major conferences (IEEEVIS, AGILE, ICC, CPGIS) Co-organizer of international workshops (e.g., GeoVIS, ISPRS AR/VR sessions) Leader of national research projects (ANR ORACLES, ANR ACTIVmap, ANR ECOCIM) Recipient of international mobility grants (AMICI I-SITE FUTURE) Contributor to national glossaries and research strategy (e.g., French photogrammetry glossary) Advising and Grants: Sidonie Christophe actively supervises PhD students and postdoctoral researchers, including Markie Jiang, Maria-Jesus Lobo, and Alexandre Mielniczek. She leads or participates in multiple funded research projects such as ANR ORACLES (marine flooding visualization), ANR ACTIVmap (tactile 3D maps), and ANR ECOCIM (eco-design of city information models). Her advisory role at the MESR involves shaping national research strategy in digital and environmental sciences. Labs and Research Teams: She is a core member of the GEOVIS team (Geovisualization, Interaction, and Immersion) at LASTIG and previously served as its leader. As co-director of LASTIG, she plays a central role in the leadership and strategic direction of the entire laboratory, which comprises over 100 researchers across four teams: ACTE, GEOVIS, MEIG, and STRUDEL.
Sao Mai Nguyen is an Enseignante-Chercheuse (Lecturer-Researcher) at ENSTA Paris, affiliated with the Unité d'Informatique et d'Ingénierie des Systèmes (U2IS). Her research bridges robotics, artificial intelligence, and cognitive science, focusing on cognitive developmental robotics, intrinsic motivation in learning, and human-robot interaction. She explores how robots can adapt to social and physical environments, particularly in physical rehabilitation and smart home applications. Research Interests: Nguyen’s work integrates machine learning, robotic embodiment, child psychology, and neuroscience. Key areas include human-robot interaction, assistive robotics for chronic low back pain rehabilitation, activity recognition in smart homes using IoT sensors, and intrinsic motivation-driven learning frameworks. Recent Contributions: Her 2024 HDR thesis on reinforcement and imitation learning for sequential tasks underscores her expertise in strategic learning systems. Recent publications address bio-inspired robotics models, hierarchical reinforcement learning, and benchmark environments like 'Open the Chests' for activity recognition. Collaborations include projects like the R-COOL randomized trial for robot-coached physical exercises. Labs & Teams: She contributes to the U2IS lab, advancing interdisciplinary research in AI and robotics. Her work spans experimental platforms for sensorimotor learning and healthcare robotics applications.
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.
Hala Lamdouar is a Research Fellow at the University of Oxford , specifically affiliated with the Institute of Biomedical Engineering (IBME). She works under the supervision of Professor Alison Noble and completed her DPhil (PhD) at Oxford's Visual Geometry Group (VGG), advised by Professor Andrew Zisserman and Professor Weidi Xie . Her academic journey began with an Engineering degree in signal and image processing from ENSEIRB-MATMECA , Bordeaux, France, followed by a Master's in applied mathematics focusing on machine learning and computer vision at Ecole Normale Superieure , Paris, where she also worked on autonomous driving perception solutions for Valeo . Education Engineering degree, ENSEIRB-MATMECA, Bordeaux MSc in Applied Mathematics (MVA), Ecole Normale Superieure DPhil (PhD), Visual Geometry Group, University of Oxford Lamdouar's research centers on Video Understanding through single and multi-modal learning, particularly in clinical settings and challenging datasets. Key contributions include motion segmentation techniques for detecting camouflaged objects, the creation of the MoCA dataset (Moving Camouflaged Animals), and scalable synthetic data pipelines for motion-based object segmentation. Her work combines ConvNets, Transformers, and optical flow analysis to address partial occlusion and motion absence in videos. Notable achievements include the Best Paper Award at the CVPR Workshop on Robust Video Scene Understanding (2021). She has published in top conferences like BMVC (2021), ICCV (2021), and ACCV (2020), with applications in biomedical imaging, autonomous systems, and unsupervised learning. Additional affiliations include the Centre for Doctoral Training in Autonomous Intelligent Machines & Systems (AIMS).
David Janin is an Associate Professor in Computer Science at Bordeaux INP , specifically within the ENSEIRB-MATMECA school. He leads the PoSET research project, exploring algebraic models for heterogeneous interactive temporal media systems. Research Affiliations : CNRS INS2I , INRIA Bordeaux Sud-Ouest , Idex Bordeaux , LaBRI (CNRS UMR 5800). Research Focus : His work bridges inverse semigroup theory and functional programming to develop algebraic frameworks for synchronizing diverse temporal media (sound, animation, video). This includes T-calculus in Haskell and Octopus for 3D animation. Technical Contributions : Key developments include models for overlapping tiles , birooted tree languages , and causal function semantics in real-time systems. Contact : janin@labri.fr
Fabrice Neyret is a senior CNRS researcher in Computer Graphics and head of the MAVERICK team (formerly ARTIS- EVASION ) within the LJK laboratory at Université Grenoble Alpes and INRIA Rhône-Alpes, France. Education PhD in Computer Science, INRIA Rocquencourt, 1996 Diplôme d’Ingénieur, Télécom Paris (ENST), 1991 DESS Ingénierie Mathématique, 1989 Maîtrise d’Ingénierie Mathématique, 1988 Licence de Mathématiques, 1987 Research Interests Neyret’s work centers on Computer Graphics with a strong focus on procedural modeling , real-time rendering of natural phenomena , and GPU acceleration . He investigates volumetric textures, clouds, smoke, rivers, lava, and forests, aiming to bridge physics-based models with efficient, user-friendly methods for video production and interactive applications. Scientific Output & Trends His publications span over two decades and highlight a consistent emphasis on real-time realistic rendering of complex natural scenes. Key themes include volumetric rendering (GigaVoxels), procedural noise, GPU-friendly algorithms, and simulation of dynamic phenomena such as convective clouds, ocean waves, and lava flows. Awards & Recognition Multiple film-festival selections for scientific visualizations (e.g., Eurographics, Festival du Film Scientifique de Palaiseau, Festival international du film scientifique de Parmes) Invited seminars at MIT, University of Toronto, University of Montréal, and others Advising & Teaching Neyret has supervised more than 30 PhD and Master students since 1997, covering topics from fractal noise rendering to large-scale volumetric visualization. He teaches in the Master DEA IVR program and offers internships and postdoc positions regularly. Teams & Labs He leads the MAVERICK research team, hosted jointly by the LJK laboratory (Université Grenoble Alpes) and INRIA . The team’s infrastructure includes access to high-end GPU clusters and collaborative links with Weta Digital and other international partners.
Thibault Tricard is an Associate Professor at Ensimag Grenoble and a permanent researcher in the Maverick team at Inria Grenoble. His work bridges Computer Graphics and Additive Manufacturing , focusing on procedural methods for virtual world content generation. His research interests include: Procedural modeling for surface and microstructure details Mesh shaders and GPU-accelerated volume rendering 3D printing optimization with staggered infill structures Recent publications like Interval Shading (HPG 2024) and Procedural Phasor Noise (ACM Siggraph 2020) highlight trends in real-time rendering and fabrication-aware procedural synthesis. Awards include the GDR IG-RV Thesis Award 2023 . He advises PhD students and collaborates with researchers such as Sylvain Lefebvre and Hans-Peter Seidel. Teaching includes GP-GPU High-Performance Computing and 3D Graphics at Inp Grenoble and UGA Mosig. Personal projects like the LavaCake Vulkan library emphasize developer accessibility.
Liming Chen is a Full Professor and Director of the Department Mathématiques - Informatique at École Centrale de Lyon, Université de Lyon. As a member of the Laboratoire d'Informatique en Image et Systèmes d'Information (LIRIS, UMR 5205), his research spans computer vision, pattern recognition, and multimedia computing. His extensive research portfolio includes 3D face analysis, image/video categorization, affect analysis, and biometric systems. He has led significant projects such as ANR 3D Face Analyzer, ANR Videosense, ANR Omnia, and ANR FAR3D, focusing on advanced recognition systems and multimodal analysis. Professor Chen supervises multiple PhD students and has developed open-source tools for 3D model processing. His work has received recognition through best performance awards at international competitions including SHREC 2011 (3D face recognition) and ImageCLEF 2011 (photo annotation).
