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Luc JaulinView profile

Professor

• Robotics
• Control Systems
• Underwater Robotics
• +4 more

Luc Jaulin is a Professor at the University Bretagne Occidentale and affiliated with Lab-STICC (UMR 6285) and ENSTA Bretagne. His research focuses on robotics, control systems, underwater navigation, and interval analysis. He leads projects in autonomous systems, such as robotic exploration (Robex) and underwater vehicle control. He has extensive teaching experience in robotics, including courses on mobile robotics, Kalman filtering, and nonlinear control. His work integrates theoretical methods with practical applications, emphasizing reliable state estimation and set-based approaches. Education and Affiliations: Professor at University of Western Brittany (ENSTA Bretagne) Laboratory: Lab-STICC, UMR 6285 Participates in the Master SDS program at Angers, focusing on robotics and automation research. Research Interests: Autonomous robotics and underwater vehicle navigation Interval analysis and set-membership methods Control systems and real-time algorithms Robot localization and SLAM Algorithm development for marine robotics Advising and Grants: Supervised over 100 students in robotics-related stages and theses. Contributed to projects like ANR ElectroKarst (underwater exploration) and Robotic Spacecraft design. Collaborates with industries (e.g., Thales, FORSSEA Robotics) and academic institutions globally. Labs and Teams: Core member of Lab-STICC and the Robex (Robotics Exploration) team, focusing on innovative robotics solutions.

Edouard LarocheView profile

Professor

• robust control
• modeling and identification
• robot control
• +4 more

Edouard Laroche is a Professor of Automation (CNU 61 section) at the University of Strasbourg, where he has been teaching since 2008. He currently serves as Deputy Director of the Faculty of Physics and Engineering since 2016 and as Training Quality Officer for the Vice President of Training and Success Pathways since 2021. His academic journey includes being a Lecturer at the Louis Pasteur University of Strasbourg from 2000 to 2008, and he earned his Doctorate from ENS Cachan in 2000 with a thesis on multi-model methodologies for the identification and robust control of asynchronous machines. His educational background includes: Engineer from the National School of Electricity and Mechanics of Nancy DEA PROTEE in 1994 Former student of ENS de Cachan/Paris Saclay Associate Professor of Electrical Engineering in 1995 DEA in science and technology teaching (1996) Authorized to direct research in 2007 with HDR on 'Identification and Robust Control of Electromechanical Systems' Laroche's research focuses on robust control, modeling and identification, robot control, flexible systems, and control of electrical systems. His primary research area since 2002 has been the robust control of flexible robots, with collaborations with G. Mercère (LIAS, Poitiers) and O. Prot (XLim, Limoges). His work addresses LPV modeling and identification of series manipulators with flexibilities, robust control across workspace, and identification and control of cable parallel robots. He has secured funding from Région Grand-Est, FEDER, CNRS PEPS IDRAC (2010-2011), and Preciput-ANR (2009). His recent publications primarily focus on university pedagogy, examining student working methods development, online teaching enhancement, cross-curricular teaching implementation, curriculum redesign, and innovative assessment methods. These works reflect his dual commitment to advancing control systems research and improving educational practices in higher education. Notable scientific contributions include organizing major conferences: CDC 2019 (1600 participants) as local organization lead, IFAC World Congress 2017 (3000 participants) as registration manager, and ECC'14 as local organization lead. He also served as animator for the 'Methods and Tools for Synthesis and Robustness Analysis' working group of the GDR MACS from 2007 to 2014. His teaching spans multiple programs: Faculty of Physics and Engineering: Automatic Control, Methodologies of University Work Telecom-Physics-Strasbourg: Continuous Automatic Control, Sustainable Engineering, Robust Control Bachelor of Science in Health Sciences: Methodologies of University Work Laroche maintains his research laboratory at ICube - AVR (Bd S. Brant, BP 10413, F-67412 Illkirch cedex) and actively offers doctoral thesis topics and internships in automation and control systems.

Andrea CavallaroView profile

Professor

• Machine Learning
• Artificial Intelligence
• Computer Vision
• +3 more

Andrea Cavallaro is a Full Professor at École Polytechnique Fédérale de Lausanne (EPFL), serving as Director of the Idiap Research Institute. His roles span academia and leadership, including directing the Centre for Intelligent Sensing and holding editorial positions in top journals. He specializes in machine learning for multimodal perception, privacy-preserving AI, and autonomous systems. Cavallaro leads projects like CORSMAL (multimodal object recognition) and GraphNEx (explainable AI). Education: PhD in Electrical Engineering from EPFL (2002). Notable awards include the Royal Academy of Engineering Teaching Prize (2007) and IEEE AVSS Best Paper Award (2009). He is a Fellow of the Higher Education Academy, International Association for Pattern Recognition, and ELLIS. Research focuses on aligning AI with societal values, particularly privacy and trustworthiness. Recent work explores adversarial attacks, privacy personas, and robotic manipulation. His 2025 publications address 3D reconstruction, privacy-aware models, and human-robot interaction. PhD students: 11 advisees in deep learning and robotics. Grants/Projects: AlignAI (trustworthy LLMs), GraphNEx (GNNs for XAI), CORSMAL (multimodal sensing). Labs/Teams: Idiap Lab (EPFL), leading CORSMAL consortium, and Turing Institute collaboration.

• Computer Vision
• Robotics
• Medical Imaging
• +3 more

Adlane HABED is an Associate Professor of Computer Science at Télécom Physique Strasbourg, University of Strasbourg, France. He is affiliated with the Control, Vision and Robotics research group within the Imaging, Computer and Engineering Sciences Laboratory (ICube UMR-CNRS 7357). His work focuses on advanced computer vision techniques, medical imaging applications, and robotics, with a strong emphasis on camera calibration, 3D reconstruction, and sensor fusion. Research interests include: - Robust camera autocalibration methods - 3D reconstruction from uncalibrated data - Medical applications in laparoscopic surgery and image-guided interventions - Optimization techniques for vision systems (e.g., LMI/SOS programming) - Sensor fusion for robotics and visual odometry Notable projects include DrAACaR, ArchZoo3D, MOSCA, and WiDop, though specific project descriptions are not provided. His work bridges theoretical computer vision with practical medical and robotic applications. Labs/Teams: Active member of the ICube laboratory's Control, Vision and Robotics group, contributing to interdisciplinary research in autonomous systems and medical imaging.

Jeff OffuttView profile

Professor

• Software Testing
• Mutation Testing
• Model-Based Testing
• +8 more

Jeff Offutt is a Professor and Chair of the Department of Computer Science at the University at Albany, part of the College of Nanotechnology, Software, & Engineering. Previously, he was a Full Professor with Tenure in Software Engineering at George Mason University, where he led the MS in Software Engineering program and developed numerous courses in software testing, web engineering, and software analysis. His research has significantly influenced both academia and industry in software testing and engineering education. His research interests span software testing, mutation testing, model-based testing, automatic test data generation, web application testing, and software engineering education. He has pioneered techniques such as bypass testing and model-based testing, with applications embedded in tools like Selenium. His work emphasizes practical, impactful research—what he calls "science fiction"—with a clear path to real-world use by software engineers. His recent publications reflect a strong trend in cost-effective mutation testing, model-based testing strategies, educational innovations like self-paced learning models (e.g., SPARC), and security aspects of web applications. The keywords across his work include software testing, empirical studies, automation, and education, with subfields such as fault localization, test oracles, input partitioning, and scalable pedagogy. John Toups Presidential Medal for Excellence in Teaching (2020) George Mason University Faculty Member of the Year (2020) Virginia Outstanding Faculty Award (2019) George Mason Teaching Excellence Award (2013) 10-year Most Influential Paper Award, MODELS 2020 Best Paper Award, ICST 2021 Most Influential Paper, ISSRE (2019) Jeff Offutt has advised numerous students and collaborated internationally, including at Swedish universities. He has led major educational initiatives such as the NSF-funded SPARC project, aimed at improving scalability and diversity in introductory CS courses. He has also been actively involved in curriculum development, including co-authoring IEEE/ACM guidelines for software engineering programs. His leadership extends to founding and chairing major conferences like IEEE ICST and serving as Editor-in-Chief of Software Testing, Verification and Reliability . He leads research projects on smart test automation, minimal mutation, and K–5 computer science integration. His work has resulted in widely used tools including muJava, Mothra, and SpecTest. He frequently gives keynote talks on testing, education, and research methodology, and is known for his popular talk "How to Get Your Paper Rejected."

Dominique VaufreydazView profile

Professor

• Multimodal Perception
• Affective Computing
• Robotics Interaction
• +5 more

Professor Dominique Vaufreydaz holds a position in Computer Science at Grenoble Alpes University and leads the Multimodal Perception and Sociable Interaction (M-PSI) team at the LIG laboratory. His academic career includes roles as Associate Professor (2005–2023) and Head of the M-PSI team. He specializes in multimodal perception, affective computing, and sociable human-robot interaction, with projects like ARAS dataset and TokenCut object discovery. Education details are not explicitly provided, but his research spans robotics, autonomous systems, and healthcare technologies. He has published extensively in top-tier conferences (CVPR, ICMI) and journals (ACM Transactions, IEEE TPAMI). Over 30 PhD students have been supervised, with current advisees exploring activity recognition, head motion generation, and emotion analysis. Teaching roles include 300+ hours annually across computer science courses (C++, databases, mobile programming) and numerical literacy for non-specialists. He co-leads the MOSIG Master's GVR specialty and manages transversal courses at the Grenoble Faculty of Economics. His labs, notably M-PSI, focus on smart spaces, ambient assisted living, and ethical teaching analytics. Notable collaborations include EU projects (FAME, CHIL) and industry partnerships like Orange Labs. His work bridges cognitive science and machine learning, with applications in healthcare and urban autonomous systems.

• Reactive Control Strategies
• Supervision and Prognosis
• Large Scale Systems
• +11 more

Eric Duviella is a Professor at IMT Nord Europe, specifically within the Department of Automatic Control and Computer Sciences. He has been a permanent faculty member since 2007 and was promoted to full Professor in 2015. His academic affiliations include strong ties with the University of Lille, Universitat Politècnica de Catalunya, and the University of Seville through collaborative research and joint Ph.D. supervision. Education: Diplôme d'Ingénieur, Ecole Nationale d'Ingénieurs de Tarbes (ENIT), 2001 M.S., Institut National Polytechnique de Toulouse (INPT), 2001 Ph.D. in Industrial Systems, Institut National Polytechnique de Toulouse, 2005 HDR (Habilitation à Diriger des Recherches), University of Lille 1, 2014 His research interests center on Reactive Control Strategies , Supervision and Prognosis , and the Modeling of Large-Scale and Environmental Systems , particularly Hydrographical and Water Systems . His work aims at predictive maintenance, adaptive management under climate change, and improving navigation and water quality through advanced control techniques. The 15 most recent publications reflect a strong trend toward Model Predictive Control (MPC) , distributed and decentralized control architectures , leak detection in water networks , and resilience of inland waterways under climate stress . Keywords across these works include control engineering, water systems, fault diagnosis, and data-driven modeling, indicating a multidisciplinary approach combining automation, environmental science, and computational intelligence. Scientific Awards: Best paper award at CODIT 2017 Eric Duviella has actively supervised numerous Ph.D. and Master’s students from institutions including IMT Lille Douai, Universitat Politècnica de Catalunya, and the University of Seville. He has led significant research grants such as GEPET-Eau, CHEEF2, and CASTR-Eau, focusing on sustainable water management, hydropower optimization, and robotic monitoring. His work often involves partnerships with agencies like VNF, EDF, and local water authorities. He is involved in key research labs and teams including the Laboratoire d'Automatique, Génie Informatique et Signal (LAGIS), and collaborates internationally through mobility programs with UPC and the University of Seville. His leadership in organizing special sessions at major conferences (e.g., IFAC, HIC) underscores his role in shaping discourse in water system control and supervision.

David BertoinView profile

Associate Professor

• Representation Learning
• Computer Vision
• Reinforcement Learning
• +2 more

David Bertoin is a Research Engineer at Photoroom, focusing on training diffusion models for image editing. He concurrently serves as a part-time Associate Professor at INSA Toulouse, where he teaches and conducts research. Previously, he worked as a Research Scientist at IRT Saint-Exupéry, contributing to the DEEL and ANITI research programs. His research interests center on representation learning, computer vision, and reinforcement learning, with a particular emphasis on improving generalization and robustness in these domains. Bertoin actively participates in academic conferences, presenting work such as Local Feature Swapping at ICLR 2022 and studies on ReLU activation functions at Neurips 2021. His GitHub repositories reflect his engagement in projects like CLOP (Local Feature Swapping) and teaching modules for M2 MAPI3. He maintains an active presence in open-source contributions related to deep learning and reinforcement learning frameworks. Education details are not explicitly provided in the text, but his professional trajectory suggests advanced qualifications in computer science or artificial intelligence. His research outputs span theoretical advancements in neural networks and practical applications in autonomous systems, cybersecurity, and drone technology. Collaborations within ANITI and DEEL highlight his involvement in interdisciplinary AI initiatives.

Jordan CARACOTTEView profile

Lecturer

• Robotics
• Computer Vision
• Artificial Intelligence
• +3 more

Jordan CARACOTTE is a Lecturer in the Perception and Robotics department at the University of Picardie Jules Verne (UPJV) . Their research focuses on advancing robotic perception through innovative computer vision techniques and sensor integration. Academic Rank: Lecturer Affiliation: Perception and Robotics, UPJV Research Interests center on photometric stereo methods , 3D reconstruction , and omnidirectional imaging for robotic applications. Key contributions include sensor fusion frameworks and marker detection systems to enhance robotic navigation and environmental interaction. Publication Trends reveal a focus on mobile robotics and vision algorithms , with works addressing panoramic camera calibration, multispectral dataset generation, and robust fiducial marker identification.

Veronique Berge-CherfaouiView profile

Professor

• Autonomous Vehicles
• Robotics
• Multi-sensor Fusion
• +3 more

Veronique Berge-Cherfaoui is a Professor at the University of Technology of Compiègne (UTC), affiliated with the Heudiasyc laboratory (UMR CNRS 7253). She holds leadership roles including Head of the Interacting Robotic Systems (SyRI) team, Scientific Manager of the Intelligent/Autonomous Vehicles platform, and Director of SIVALAB—a joint Renault-UTC-CNRS laboratory. Previously, she led the Real-Time Systems and Embedded Computing (STRIE) department of Computer Engineering until 2021. Her research centers on autonomous vehicle systems , with expertise in multi-sensor fusion , uncertainty management , trajectory planning , and perception integrity . Her Authorization to Direct Research (2009) focused on uncertainty management in sensor fusion, forming the foundation for her work in intelligent transportation systems. Current projects address operational domain integrity monitoring and robust trajectory planning under real-world constraints. Professor Berge-Cherfaoui has supervised 35 doctoral and master’s students, with research spanning: Cooperative human-machine control (MESR/PSA grants) Collaborative perception (Renault/labex MS2T grants) Evidential perception using machine learning (Renault) Dynamic local map fusion (DGA/labex MS2T) Funding sources include Renault, Stellantis, PSA, CNRS, MESR, DGA, and regional grants. She directs SIVALAB and leads the SyRI research team at Heudiasyc, while serving on scientific councils for CNRS’s INS2I institute and CEESAR (European Center for Security Studies and Risk Analysis).

• Systems Control
• Embedded Software Design
• Embedded Systems Performance Analysis
• +5 more

Fouad KHENFRI is a Professor and researcher at ESTACA (Ecole Supérieure des Techniques Aéronautiques et de Construction Automobile) , specializing in embedded systems and control engineering. He holds a PhD in Computer Science and Applications from the University of Nantes (2016), a Master's in Automatic Control from EMP Algiers (2011), and an Engineering Degree in Automation from the University of Biskra (2008). Key research areas: Systems Control, Embedded Software Design, and Artificial Intelligence Recent publications focus on UAV control systems, Neural Architecture Search, and energy optimization Supervising doctoral students on topics including drone development and deep learning applications

Bruno GasView profile

Professor

• Robotics
• Artificial Intelligence
• Sensorimotor Learning
• +3 more

Bruno Gas serves as a Professor at Sorbonne University, affiliated with the ASIMOV research team within the Intelligent Systems and Robotics Institute (ISIR). His academic work bridges robotics, artificial intelligence, and cognitive science through innovative investigations into sensorimotor learning frameworks for embodied agents. Gas's research centers on how naive robotic agents develop spatial and bodily representations through sensorimotor interactions, with particular emphasis on multimodal sensory integration (audition, vision, and touch). His work demonstrates how robots can autonomously construct internal models of their environment through active exploration, utilizing principles from developmental psychology and neuroscience. Key methodologies include neural network modeling, predictive processing architectures, and bio-inspired sensorimotor contingency frameworks that enable agents to learn without pre-programmed spatial knowledge. Analysis of Gas's recent publications (2013-2020) reveals consistent thematic progression in developmental robotics, focusing on the emergence of topological spatial representations, active exploration strategies, and multimodal sensor fusion. His research demonstrates how sensorimotor flow generates internal spatial models, with notable contributions including the Head Turning Modulation System for environment exploration and tactile space representation models. This work establishes critical links between robotics, cognitive science, and neuroscience through experimentally validated frameworks for embodied learning. No explicit information regarding student supervision or research grants appears in the source material, though extensive collaborative publications with researchers like Sylvain Argentieri and J. Kevin O'Regan suggest active mentorship and project leadership within the ISIR ecosystem. His publication record shows sustained interdisciplinary collaboration across European robotics institutions. Gas operates within the ASIMOV team at ISIR (Institut des Systèmes Intelligents et de Robotique), a premier robotics research unit jointly operated by Sorbonne University and CNRS. The team specializes in adaptive systems and intelligent machines, with research spanning embodied cognition, developmental robotics, and human-robot interaction. ASIMOV's experimental platforms focus on sensorimotor learning paradigms for autonomous exploration, positioning Gas at the forefront of bio-inspired robotics research in France.

Scotto CécileView profile

Researcher

• Motor Control and Learning
• Sensorimotor Control
• Multisensory Integration
• +5 more

Cécile Scotto is a researcher affiliated with the University of Poitiers, specifically within the Cognition and Learning Research Center (CeRCA) under the Faculty of Humanities and Social Sciences. Her work focuses on sensorimotor control, motor learning, and multisensory integration, with applications in human-machine interactions and ergonomic design. She holds an HDR (Habilitation à Diriger des Recherches) in cognitive sciences. Her research explores topics such as the impact of visual and proprioceptive feedback on motor learning, the effects of environmental factors like temperature on sensorimotor performance, and perceptual biases arising from cross-modal interactions (e.g., visual-tactile). She collaborates with industries to develop reproducible evaluation scenarios for human-robot interfaces and industrial maintenance systems. Key contributions include studies on motor adaptation in deafferented patients, the role of gravity in spatial orientation, and the neural mechanisms underlying tool-use anticipation. Her publications frequently address interdisciplinary themes spanning neuroscience, ergonomics, and robotics. Teaching activities include courses on Psychology of Movement, Sensory Deficits, and Motor Control at undergraduate and graduate levels. While no formal awards are listed, her extensive publication record reflects sustained research excellence across over a decade. Labs/Teams: Active member of CeRCA, collaborating with institutions like the Institute of Psychology and Neuroscience of Lyon (UMR 5229), and industry partners in robotics and human factors engineering.

• Robotics
• Computer Vision
• Autonomous Systems
• +3 more

Lucia BERGANTIN is an Enseignant Chercheur (Teaching and Researcher) in the Computer Science department at IMT Atlantique, based at the Brest campus. Her work focuses on robotics, computer vision, and biomimetic systems, particularly leveraging optic flow algorithms for navigation and control in autonomous systems. Her research explores applications in underwater vehicles, aerial robotics, and bio-inspired models derived from insect behavior. Her research interests span robotics control, sensor integration, and autonomous navigation systems. Notably, she investigates optic flow-based odometry for both indoor/outdoor environments and underwater missions, emphasizing real-time performance and reliability across varying trajectories. Lucia’s publications highlight contributions to oscillatory trajectory modeling, biomimetic visual systems, and sensor fusion strategies. Her work often bridges theoretical models with practical implementations in robotics, aiming to enhance autonomous systems’ adaptability and precision in dynamic environments. Her advising and grants are not explicitly detailed in the provided texts, but her department (Computer Science) at IMT Atlantique is part of the Institut Mines-Télécom network, indicating potential collaborative research opportunities. Her research aligns with broader institutional priorities in digital and environmental transitions.

• Distributed Systems
• Networks
• Data Stream Analysis
• +9 more

Yann Busnel is a Full Professor at IMT Atlantique in France, where he serves as Head of the Network Systems, Cyber Security and Digital Law (SRCD) department at the Rennes Campus since January 2017. He also leads the D2-NTS department (Networks, Telecommunications and Services) within UMR IRISA. His academic journey includes positions as Assistant Professor at Université de Nantes (2009-2014), Associate Professor and Head of Computer Science Department at ENSAI (2014-2016), and postdoctoral work at Università "La Sapienza" in Rome. Busnel's research focuses on models for large-scale distributed systems and networks, with particular expertise in data stream analysis over massive datasets. His work spans cybersecurity, dependability, medical data analysis (including pharmacovigilance and genomic sequence analysis), and the self-organized coordination of drone fleets for disaster management. He has published over 100 peer-reviewed papers and coordinated numerous national and international research projects. His recent scholarly output demonstrates a clear progression toward applied cybersecurity solutions, particularly in federated learning for intrusion detection, blockchain analysis, and wireless network security. The research shows strong interdisciplinary connections between distributed systems theory and practical security applications, with increasing emphasis on medical data analysis and drone coordination systems. His work bridges theoretical computer science with real-world security and networking challenges. Busnel actively mentors PhD students across multiple institutions, with current advisees working on topics including AI in cybersecurity using game theory, threat intelligence tools for IoT, and trust in distributed network services. He has coordinated substantial research funding through projects like CMA TCE (France 2030), EDIH Bretagne (Horizon Europe), and various ANR-funded initiatives. He leads several research chairs including OM&AI2MD (Operations Models and Artificial Intelligence to Manage Disasters), PRACom (Pôle de Recherche Avancée en Communications), and Cyber CNI (Cyber Security of Critical Infrastructures), demonstrating his leadership in both academic research and industry collaboration. His work with these chairs focuses on practical applications of his theoretical research in disaster management, communications technology, and critical infrastructure protection.