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Edouard OyallonView profile

Researcher

• Machine Learning
• Deep Learning
• Distributed Systems
• +5 more

Edouard Oyallon is a CNRS Researcher at Sorbonne University's MLIA team within the Institute of Intelligent Systems and Robotics (ISIR). His research focuses on machine learning foundations, particularly the symmetries of deep neural networks, and large-scale distributed/decentralized training algorithms. He has contributed to frameworks like Kymatio for wavelet scattering transforms and collaborates on projects such as SHARP (Frugal Learning) and ADONIS (ANR-funded). He advises multiple PhD and postdoctoral researchers and teaches advanced deep learning courses at Institut Polytechnique de Paris (IPP). Grants include the ADONIS project (ANR/Sorbonne) and participation in VHS and CoCa4AI initiatives. His work spans theoretical and applied aspects, with recent emphasis on optimizing LLM training at exascale. He maintains active roles in academic service, including organizing workshops on federated learning and graph machine learning.

David GesbertView profile

Professor

• Communication theory
• Signal processing for wireless networks
• Information theory
• +7 more

David Gesbert serves as Professor and Director of EURECOM, a leading research institution in Sophia Antipolis, France, specializing in digital sciences. Previously heading the Communications Systems Department, he now directs EURECOM while leading the Foundations & Algorithms research group within the Communication Systems Department. His leadership spans institutional administration and cutting-edge research supervision. Dr. Gesbert's research portfolio demonstrates exceptional depth across communications theory and wireless networking: Communication theory and information theory fundamentals Signal processing for wireless networks with emphasis on robustness Machine learning applications for decentralized network optimization Connected robotics and UAV-enabled flying radio access networks 6G wireless architecture with focus on AI integration Distributed decision making under information uncertainties His publication trajectory reveals a strategic evolution from classical communication theory toward AI-integrated wireless systems, particularly focusing on UAV-aided networks and connected robotics for 6G. Recent work emphasizes learning-based approaches for network optimization under asymmetric information conditions, with growing emphasis on sustainability and green communications. Dr. Gesbert's scientific recognition includes: Fellow of IEEE (2011) and Asia Pacific Artificial Intelligence Association (2021) Thomson-Reuters List of Highly Cited Researchers in Computer Science Multiple Best Paper Awards at IEEE conferences (EW 2017, ICC 2019) ERC Advanced Grant recipient for the PERFUME project on Smart Device Communications 3IA Chair funding for AI for future IoT Networks 2019 Winner of 'Fundamental research project of the year' by French SCS He actively mentors PhD students and researchers, welcoming collaboration in his research domains. His group secures substantial research funding including ERC grants, 3IA Chairs, and participation in major European projects like the WINDMILL ITN Marie Curie project on Machine Learning in Wireless Communications. Dr. Gesbert serves on editorial boards and regularly delivers keynotes at premier international conferences, establishing himself as a thought leader in next-generation wireless communications.

Véronique PerdereauView profile

Professor

• Robotics
• Dexterous Manipulation
• Tactile Feedback Systems
• +4 more

Véronique Perdereau is a Full Professor at Sorbonne Université's Institute of Intelligent Systems and Robotics (ISIR) , specializing in robotics and dexterous manipulation. She leads the ASIMOV research team and serves as a principal investigator for multiple European projects, including SOFTMANBOT, INDEX, and CORSMAL, focusing on tactile feedback, multimodal control, and human-robot interaction. Role: Full Professor (2024) Email: veronique.perdereau@sorbonne-universite.fr Office: H13, Campus Pierre et Marie Curie, Paris Research Focus Perdereau's work centers on tactile-driven robotic control systems, human-inspired manipulation strategies, and multimodal fusion for industrial automation. Her research bridges theoretical modeling (e.g., Cosserat mechanics, dual quaternions) with practical applications in manufacturing sectors. Key Themes: Tactile Feedback Systems Dexterous In-Hand Manipulation Human Motion Data Integration Autonomous Grasp Stability Flexible Object Handling Reproducibility in Robotic Experiments Notable Projects She has spearheaded projects like: SOFTMANBOT (2019–2023): Advanced robotic technology for handling soft materials in manufacturing. INDEX (2019–2022): Developing motor action dictionaries for robotic hands. CORSMAL (2019–2022): Multimodal fusion for collaborative object recognition. Scientific Leadership Perdereau has led work packages in 10+ international collaborations with institutions across Europe, including Decathlon, IIT, and Queen Mary University. Her research emphasizes safety, ethics, and industry 4.0 applications.

• Robotics
• Autonomous Vehicles
• Data Fusion
• +3 more

Philippe BONNIFAIT is a Professor at the University of Technology of Compiègne (UTC) and Director of the Heudiasyc Research Lab (UMR UTC-CNRS 7253) since 2018. He specializes in robotics, autonomous vehicles, and data fusion, with a focus on localization systems and sensor integration. His research addresses challenges in intelligent transportation, fault detection, and cooperative robotics. He holds leadership roles including Head of the Autonomous Land Robotics axis in the TIRREX EQUIPEX+ project, and serves on the steering committee of the SIVALab joint lab with UTC, CNRS, and Renault. His international collaborations include Coimbra University (Portugal). Research Interests: Autonomous Vehicle Navigation Multi-Sensor Fusion GNSS-Based Positioning Decentralized Cooperative Systems Intelligent Transportation Systems Publications highlight advancements in vehicle localization, error mitigation, and sensor integration for autonomous systems. Notable work includes fault detection methodologies and HD map-aided navigation. No scientific awards listed. Active in lab administration and industry partnerships, contributing to experimental vehicles and robotics infrastructure.

François GouletteView profile

Professor

• 3D Point Cloud Processing
• LiDAR Perception
• Autonomous Systems
• +7 more

François Goulette is a Professor and Deputy Director of the Computer Science and Systems Engineering Unit (U2IS) at ENSTA Paris, part of Institut Polytechnique de Paris. His research focuses on 3D point cloud processing, LiDAR perception, and autonomous systems within the Robotics Center (CAOR). His primary research interests lie in 3D point cloud processing , LiDAR perception , and autonomous systems . His work spans fundamental algorithm development to practical applications in autonomous driving, cultural heritage digitization, and robotics. He has made significant contributions to domain generalization of LiDAR perception, semantic segmentation of 3D point clouds, and point cloud registration techniques. The analysis of his recent publications reveals a strong focus on domain generalization for LiDAR perception systems, with multiple papers addressing challenges in 3D semantic segmentation across different environments. His work combines multi-scale architectures , unsupervised learning , and dataset creation to advance the state-of-the-art in autonomous systems perception. The research spans both theoretical algorithm development and practical applications in urban environments. François Goulette leads research activities within the Robotics Center (CAOR) at ENSTA Paris. His team develops advanced techniques for 3D environment understanding, with applications in autonomous vehicles, cultural heritage preservation, and industrial robotics. The research combines computer vision, machine learning, and robotics to solve challenging problems in 3D perception and scene understanding.

• Robotics
• Computer Vision
• Machine Learning
• +4 more

Nicolas RAGOT is an Associate Professor at CESI, affiliated with the Engineering and Numerical Tools department. He teaches Digital and embedded electronics, Microcontroller programming, System control, and Sensors at the Bachelor and Master levels. His research focuses on Environment perception for robotics and Computer vision, particularly in unconventional applications. He leads or collaborates on major research programs including ROJUNACO (2023–2025), FUSION (2023–2027), OASIS (2022–2024), and COLIBRY (2021–2024), all addressing robotics, digital twins, and industrial automation. He co-supervises PhD students Y. Feddoul, S. Ouarab, and S. Choudhary. His work spans smart mobility, assistive technologies, and energy-efficient systems. He is a member of the Secure Electronic Transactions (TES) competitiveness cluster's expert committee. Education: PhD in Computer Vision (University of Rouen, 2009), Master in Electrical Engineering (University of Paris XI, 2003), Engineering diploma (ESIGELEC, 1999). Research interests emphasize robot perception, human-robot collaboration, and extended reality integration. His publications span object detection, SLAM algorithms, and smart wheelchair systems. Current projects emphasize industrial robotics, digital twins, and real-time 3D reconstruction. Advising and grants include leadership roles in multiple research programs and co-supervision of three PhDs. His lab work focuses on Engineering and Numerical Tools, with contributions to CESI LINEACT's collaborative robotics initiatives.

Thi Phuong Khanh NguyenView profile

Researcher

• Prognostics and Health Management (PHM)
• Predictive Maintenance
• Condition-Based Maintenance
• +8 more

Dr. Thi Phuong Khanh Nguyen is a researcher at the Ecole Nationale d'Ingénieurs de Tarbes (ENIT) , affiliated with the College of Engineering and Department of Systems . Her work focuses on Prognostics and Health Management (PHM) , predictive maintenance, and industrial data analytics, combining machine learning with physics-informed modeling to address uncertainty in system degradation. Teaching: Mathematics for engineers, Probability, Statistics, Operating safety Research: Health indicators, diagnostics, prognostics, multimodal data fusion Methods: Data mining, physical and data-driven models, decision support systems Tools: FAST, Petri nets, UML, HMM, RNN, CNN, Transformer architectures Her recent publications highlight advancements in explainable AI , physics-informed neural networks , and multimodal learning for fault detection, battery RUL prediction, and robotic inverse dynamics. She also explores blockchain and federated learning for decentralized prognostics.

• Robotics
• Underwater Robotics
• Computer Vision
• +7 more

Claire Dune is an Assistant Professor at the University of Toulon, affiliated with the COSMER Laboratory (Mechanical and Robotic Systems Design Laboratory). Her research focuses on robotics, computer vision, and underwater systems, with applications in environmental monitoring and human-robot interaction. She teaches computer science, numerical methods, image processing, and visual servoing. Institution: University of Toulon Laboratory: COSMER (Mechanical and Robotic Systems Design Laboratory) Academic Rank: Assistant Professor Email: claire.dune@univ-tln.fr Her research centers on perception for robot control, particularly in underwater robotics and computer vision. Key interests include visual servoing, SLAM, gesture recognition for diver-robot interaction, and autonomous capabilities in real-world marine environments. She applies deep learning and sensor fusion techniques to enhance underwater visual perception and navigation. The recent publications demonstrate a strong trend in underwater robotics, with focus areas including tether dynamics (catenary modeling), ROV localization using umbilicals and IMUs, long-term visual localization in deep-sea environments, and color restoration in underwater imagery. Her work bridges theory and real-world application, contributing datasets like 'Eiffel Tower' for benchmarking and advancing multi-agent SLAM systems. Claire Dune has contributed to leading journals such as IEEE Robotics and Automation Letters, Ocean Engineering, and The International Journal of Robotics Research. Her editorial and survey work highlights her leadership in the domain of deformable object manipulation. Retrieval of benthic habitat abundance and bathymetry from hyperspectral data (DESIS) in shallow waters ROV localization using ballasted umbilical equipped with IMUs MAM3SLAM: Towards underwater robust multi-agent visual SLAM Eiffel Tower: A Deep-Sea Underwater Dataset for Long-Term Visual Localization Challenges and Outlook in Robotic Manipulation of Deformable Objects Claire Dune actively collaborates with researchers such as Vincent Hugel, Juliette Drupt, and Andrew Comport. She has supervised or co-supervised numerous research projects and publications, particularly in underwater robotics and assistive technologies. Her work involves experimental robotics and system integration, often validated in real marine environments. She leads research in the COSMER laboratory focused on underwater robotics, including projects on tethered ROVs, diver-robot communication via gesture recognition, and environmental monitoring using visual and hyperspectral data. Her team develops practical solutions for marine science and offshore operations, emphasizing robustness and autonomy.

• Computer Vision
• Robotics
• 3D Reconstruction
• +4 more

El Mustapha Mouaddib is a Professor in the Perception and Robotics department at Universite de Picardie Jules Verne, affiliated with Laboratory Heudiasyc (UMR CNRS 7253). His research bridges advanced robotics with cultural heritage preservation, focusing on developing novel computer vision techniques for complex documentation challenges. His primary research interests include omnidirectional vision systems , hyperspectral imaging , and 3D reconstruction methodologies , with significant emphasis on applications for cultural heritage documentation. Mouaddib's work particularly addresses challenges in temporal illumination compensation , laser scanning registration , and multi-scale digitization of historical structures, as evidenced by his extensive Notre-Dame de Paris cathedral research. Analysis of his 15 most recent publications reveals a consistent trajectory toward heritage robotics - developing specialized computer vision algorithms for cultural preservation. His work demonstrates increasing sophistication in integrating multi-modal sensor data (TLS, hyperspectral, RGB-D) solving illumination challenges in historical documentation developing adaptive robotic systems for complex environments Notably, his Notre-Dame research forms a cohesive body of work examining structural changes through advanced 3D analysis. Mouaddib actively participates in major interdisciplinary projects including SAMURAI , ASSIDUITAS , SCANBOT , ADAPT , and SUMUM , which focus on heritage digitization and robotic exploration. His collaborative approach is evident through extensive co-authorship with institutions like CNRS and international partners in Japan and Italy. His laboratory work centers on the E-Cathedrale initiative, creating comprehensive digital twins of Gothic cathedrals through multi-temporal and multi-scale documentation. This involves developing specialized hardware (like the HDROmni camera system) alongside novel algorithms for processing challenging heritage environments.

Julien MoreauView profile

Lecturer

• Computer Vision
• Robotics
• Autonomous Vehicles
• +4 more

Julien Moreau is a Lecturer at the University of Technology of Compiègne (UTC), affiliated with the Heudiasyc-SyRI laboratory (UMR CNRS 7253). His research focuses on computer vision, robotics, and autonomous vehicle systems, particularly in sensor calibration and 3D modeling. His work includes the PFSeq dataset, a photorealistic fisheye sequence for evaluating self-calibration and stereo matching, developed during his PhD thesis. He has contributed to advancements in camera-LiDAR fusion and urban localization algorithms. Recent achievements include a paper accepted for oral presentation at BMVC 2023 titled PseudoCal: Towards Initialisation-Free Deep Learning-Based Camera-LiDAR Self-Calibration , co-authored with Mathieu Cocheteux and Franck Davoine. Julien participates in academic collaborations, including organizing interdisciplinary events like the trans-GdR ISIS and Robotics day on 'Event camera applied to robotics'. His current research is supported by the ANR MEDDTL PREDIT CAPLOC project.

Guillaume CaronView profile

Associate Professor

• Robotics
• Computer Vision
• Machine Learning
• +5 more

Guillaume Caron is an Associate Professor at the Université de Picardie Jules Verne (France) and holds a delegation at the CNRS-AIST Joint Robotics Laboratory (JRL) in Tsukuba, Japan. He leads the Perception team at JRL since April 2021 and co-directs the laboratory since 2022. His academic roles include being an enseignant-chercheur (lecturer-researcher) in robotic vision and habilitated to supervise research. He has collaborated with institutions like AIST, INRIA, and companies such as Kawasaki Heavy Industries and Thales Optronique SA. Research Interests : His work focuses on robotic vision systems, adaptive cameras, visual servoing, and applications in cultural heritage preservation and medical robotics. He develops advanced imaging techniques (e.g., hyperspectral, omnidirectional) and integrates them into robotic systems for tasks like autonomous navigation, object manipulation, and assistive technologies. Recent projects include spherical vision-based wheelchair assistance and teleoperated humanoid robots in nursing contexts. Publications : His most recent work addresses multimodal navigation leveraging large language models, spherical image representations for robotics, and illumination compensation in hyperspectral imaging. He also explores cybernetic avatars for telepresence and modular assistive smart wheelchairs. Responsibilities : He co-organizes workshops on e-Heritage and chairs the IAPR Technical Committee on Computer Vision for Cultural Heritage. He serves on the CNRS-AIST JRL steering committee and the AFRIF administration board. His educational roles include leading the RVI professional license program at UPJV until 2019. Labs/Teams : Active in the MIS laboratory (Amiens) and the CNRS-AIST JRL, working on projects like the Coalas neuro-rehabilitation system and the MuSeM multispectral dataset for mobile robotics.

Mohammed Nabil EL KORSOView profile

Professor

• Statistical Signal Processing
• Machine Learning
• Detection and Estimation Theory
• +5 more

Mohammed Nabil EL KORSO is a Professor at CentraleSupélec, part of the University of Paris-Saclay. He is affiliated with the Laboratoire des Signaux et Systèmes (L2S). His research focuses on statistical signal processing, machine learning, detection/estimation theory, and robust signal processing, with applications in radioastronomy, radar systems, and source localization. He has contributed extensively to methodologies like Kalman filtering, covariance estimation, and array processing. His work emphasizes robust techniques for handling non-Gaussian noise and interference, particularly in radio interferometry and SAR imaging. Key contributions include algorithms for array calibration, RFI mitigation, and subspace estimation. His research also addresses challenges in distributed and adaptive signal processing, with applications to vital signs monitoring and robotic systems. He has published over 50 journal articles and conference papers, focusing on performance bounds (Cramér-Rao, Weiss-Weinstein), Bayesian methods, and practical implementations for large-scale systems. His recent work includes advancements in low-cost interferometric imaging and phase estimation for SAR time series. EL KORSO collaborates with international projects like the Square Kilometre Array (SKA), contributing to technological developments in radio astronomy. He supervises research in signal processing labs and actively participates in academic conferences such as EUSIPCO and ICASSP.

Fabien MoutardeView profile

Professor

• Machine Learning
• Deep Learning
• Computer Vision
• +8 more

Fabien Moutarde is a Full Professor and Director of the Center for Robotics at MINES ParisTech (PSL University, Paris, France). He holds a PhD in Physics and an Habilitation to Direct Research in Engineering Sciences. Dr. Moutarde coordinates French engineering education at ParisTech_Shanghai (SPEIT) in China. Research Areas Deep Learning & Reinforcement Learning Computer Vision for Intelligent Vehicles Collaborative Robotics Traffic Analysis & Forecasting Human Gesture Recognition Recent Article Trends His work focuses on autonomous driving using Deep Reinforcement Learning, pedestrian trajectory prediction with spatio-temporal attention, and multi-modal localization techniques combining vision with Wi-Fi. Key applications include urban traffic analysis, collaborative robotics, and end-to-end driving systems. Leadership & Teaching Co-created specialized Machine Learning courses Pioneered Deep Reinforcement Learning lectures Led French-Chinese academic coordination Former UML/Java curriculum developer Publications With 28 h-index, his research includes 30+ IEEE/ACM publications on autonomous vehicles, gesture recognition, and traffic mining. Representative conferences: CVPR, NeurIPS, IROS, ITSC.

• Robotics
• Control Systems
• Unmanned Aerial Vehicles
• +3 more

Pascal Morin serves as a University Professor at Sorbonne University within the Faculty of Science and Engineering. He is an active member of the ASIMOV research team at the Intelligent and Robotic Systems Institute (ISIR), located at 4 Place Jussieu in Paris. His office H17 serves as the base for his research activities in advanced robotics and control systems. Professor Morin's research focuses on cutting-edge robotics applications, particularly in unmanned aerial vehicle navigation and control systems. His work spans nonlinear control theory, visual servoing techniques, and micro air vehicle development. Key interests include homography estimation for image stabilization, thermal anemometry for airflow sensing, and obstacle avoidance algorithms for precision robotics. His publications demonstrate consistent innovation in combining theoretical control frameworks with practical robotic implementations. Analysis of his 15 most recent publications reveals strong thematic continuity in UAV navigation systems, with increasing integration of deep learning techniques since 2020. His work consistently addresses GPS-denied environments and sensor fusion challenges, with notable contributions to thermal-based odometry and visual-inertial navigation systems. The research trajectory shows progression from theoretical control frameworks toward increasingly complex real-world applications including power line inspection and microscopy manipulation. Professor Morin actively collaborates with major aerospace institutions including ONERA and DLR, as evidenced by his participation in the EuRoC challenge. His editorial work on MAV navigation special collections demonstrates leadership in the micro air vehicle research community. While specific grant details aren't provided in the source material, his sustained publication output across multiple high-impact journals indicates successful funding acquisition. As a core member of the ASIMOV team at ISIR, Professor Morin contributes to Sorbonne University's leadership in robotics research. The team maintains strong industry connections through publications in Aerospace Lab and collaborations with organizations like AIAA. Current research directions appear focused on thermal sensor integration for MAVs and nonlinear control solutions for challenging operational environments.

• Optimization
• IoT
• Sensors
• +3 more

ZGHAL Mourad is a Researcher-Lecturer at CESI LINEACT, holding an HDR (2008) from Sup’Com, Carthage University and a PhD in Electrical Engineering (2000) from University Tunis Manar. He specializes in Optimization, IoT, Sensors, and Smart Healthy Cities , with a strong focus on Photonic Crystal Fibers and Nonlinear Optics . Education: HDR in Engineering (2008), Sup’Com, Carthage University PhD in Electrical Engineering (2000), University Tunis Manar Engineering Degree in Telecommunications (1995), Sup’Com, Carthage University Research Interests: Mourad’s work bridges IoT sensor networks with optical communication systems . He pioneers mid-infrared supercontinuum generation in chalcogenide fibers and explores optical mode multiplexing for high-speed communications. His recent work integrates federated learning for intrusion detection in smart grids and optimizes photovoltaic energy systems for building decarbonization . Publications Trends: His 2023–2025 work emphasizes AI-driven energy management , cybersecurity for IoT , and federated learning frameworks . Earlier contributions (2016–2019) focused on nonlinear optical effects in photonic fibers and high-bit-rate networks . Awards: Elected Vice-Präsident of the International Commission for Optics Fellow Optica (ex OSA) and SPIE Associate scientist at ICTP (UNESCO Category 1 Institute) Advising & Grants: Supervised 9 PhD students (e.g., Z. MONLA’s work on BIM/VR in building maintenance). Active member of the LINEACT Scientific Council and CTI Commission des Titres d’Ingénieurs. Labs & Teams: Leads the Engineering and Numerical Tools research team at CESI LINEACT. Collaborates with IMT Télécom SudParis as an Adjunct Professor.