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.
Paul-Eric DOSSOU is a Researcher at ICAM’s Grand Paris Sud campus, specializing in Societal and Technological Transitions of Companies. His work focuses on Industry 5.0, decision-aided systems, logistics optimization, and digital twin applications. He leads projects like Plateforme Life, Urban Logistics, and Healthcare 4.0, aiming to enhance SME efficiency through sustainable digital transformation. Expertise includes AI-driven supply chain management, cybersecurity for legacy systems, and robotic solutions for archaeology. He collaborates with industry partners to bridge theoretical research and practical applications, emphasizing human-centric automation and environmental sustainability. Contact: paul-eric.dossou@icam.fr | Mobile: +33 6 17 81 33 43 Research contributions span over 30 peer-reviewed articles since 2003, addressing topics from energy audits in the nautical industry to multi-agent systems in supply chain optimization.
Stéphane Doncieux is a University Professor in Computer Science at Sorbonne University, where he is affiliated with the Institute of Intelligent Systems and Robotics (ISIR), a joint research laboratory with CNRS. Since January 2024, he has served as Director of ISIR, following a term as Deputy Director from 2019 to 2023. He leads the ASIMOV research team and is based at the Pierre and Marie Curie Campus in Paris. His primary research interests lie in cognitive and developmental robotics, with a strong focus on open-ended learning, evolutionary algorithms, and adaptive systems. He investigates how robots can autonomously learn diverse skills through mechanisms such as novelty search, quality-diversity optimization, and intrinsic motivation. His work bridges theoretical foundations in artificial life and practical applications in robotic manipulation, perception, and control. The recent publications highlight a consistent trend in advancing robotic learning under sparse rewards and in open-ended environments. Key themes include quality-diversity optimization for grasping, state representation learning, sim-to-real transfer, and the development of behavioral repertoires. These works are published in high-impact journals such as IEEE Transactions on Robotics, Evolutionary Computation, and Frontiers in Robotics and AI. Coordinator, DREAM FET H2020 project (2015–2018) Principal Investigator, ANR projects on Creative Adaptation by Evolution, Learning Movement Skills, and Grasping with Multimodal Feedback Involved in European initiatives including VeriDREAM and HumanE-AI-Net He has supervised numerous PhD and Master’s students, including Leni Le Goff, Giuseppe Paolo, Alban Laflaquière, and Achkan Salehi, often in collaboration with leading researchers like Olivier Sigaud and Jean-Baptiste Mouret. He teaches computer science and robotics at both undergraduate and graduate levels at Sorbonne University. Doncieux has been instrumental in shaping research directions in evolutionary and developmental robotics, notably through his leadership in the IEEE Task Force on Evo-Devo-Robotics and his editorial contributions. His lab, ASIMOV, fosters interdisciplinary research integrating computer science, neuroscience, and engineering to create more autonomous and intelligent robotic systems.
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.
Alexandre PARANT is a Researcher at the University of Reims Champagne-Ardenne, affiliated with the School of Engineering and Digital Tools. His work focuses on cyber-physical systems, digital twins, and industrial automation, with a strong emphasis on the IEC 61499 standard for control architecture development. Research Themes: Model-driven engineering for production systems Digital twin implementation IEC 61499 standard application Modular cyber-physical systems Article Trends: Alexandre's publications span model-based development, robotics synchronization, and PLC identification. His work bridges theoretical modeling with practical automation solutions, particularly in educational contexts and industrial manufacturing. Labs & Teams: LINEACT research team Collaboration with CESI Campus Reims
Bastien Berret is a Full Professor at the University of Paris-Saclay, where he leads the MHAPS research team within the Faculty of Sports Sciences. His academic career has progressed from Assistant Professor at Univ. Paris-Sud (2012-present) to Associate Professor with Habilitation à Diriger des Recherches (HDR) in 2017, and finally to Full Professor in September 2020. His research focuses on understanding how the central nervous system controls voluntary movements through a multidisciplinary approach combining neuroscience, biomechanics, and robotics. From a fundamental perspective, he identifies computational principles to explain human behavior in various motor tasks, with practical applications in human-exoskeleton interactions. His work employs computational tools including stochastic optimal control, numerical optimization, and machine learning methods, alongside experimental tools such as motion capture devices, force platforms, and electromyography systems. Berret's publication record shows consistent output since 2008, with particular productivity in recent years (2020-2023). His research trends indicate a strong focus on motor control theory, gravity effects on movement, human-exoskeleton interaction, and computational modeling of neural processes. Recent publications demonstrate increasing interdisciplinary collaboration across neuroscience, robotics, and biomechanics. Notable scientific achievements: Junior member of the prestigious Institut Universitaire de France (IUF) from 2017-2022 Coordinator of the ANR project "EXOMAN" (2020-2024) Extensive publication record in high-impact journals including Science Advances, PLoS Computational Biology, and Journal of Neurophysiology Berret maintains active research collaborations with institutions including INSERM, Istituto Italiano di Tecnologia, and various neuroscience laboratories. His work on stochastic optimal control and muscle activity decomposition has contributed significantly to computational neuroscience methodology. As team leader of MHAPS, he directs research on motor control principles and their applications in rehabilitation and robotics.
Dr. Ekta Singla is an Associate Professor and Head of the Department of Mechanical Engineering at the Indian Institute of Technology Ropar (IIT Ropar), where she has been serving since 2010. She holds a PhD from IIT Kanpur (2010), an M.Tech from Thapar University (2002), and a B.Tech from Punjab Technical University (2000). She has held visiting and research positions at SUNY New York, University of Pierre and Marie Curie (Paris), and TU Berlin, and has over fifteen years of experience in robotics and applied optimization. PhD, Indian Institute of Technology Kanpur, India, 2010 M.Tech, Thapar University, Punjab, India, 2002 B.Tech, Punjab Technical University, India, 2000 Her research focuses on modular robotics, service robots, assistive devices, rehabilitation robotics, and optimal synthesis of manipulators. She is particularly interested in task-based design, motion planning, and hybrid morphologies. She leads innovative projects in medical and defence robotics, supported by industrial partnerships and international collaborations with the University of Stony Brook (New York) and UK-India initiatives. Dr. Singla has established a robotics research and training center at IIT Ropar through an MoU with Tata Automation Ltd. She founded PUNJRobotics, an interdisciplinary network promoting robotics innovation across regional institutes. Her editorial contributions and participation in professional societies reflect her growing influence in the robotics community. Institute Gold Medal (M.Tech) National Doctoral Fellowship (PhD) CNRS Postdoctoral Fellowship National Award from Institute of Engineers She has completed four major research projects and has been actively involved in academic administration, including student and academic affairs. She also serves as Convener for BAJA SAEINDIA Ropar 2018. Her work bridges theoretical robotics with practical industrial and medical applications, enhancing both training and innovation at IIT Ropar. Dr. Singla leads a dynamic research group focused on real-world robotic applications, with active collaborations and an emphasis on interdisciplinary training and regional outreach through PUNJRobotics.
Noury Bouraqadi is a part-time university professor at IMT Nord Europe, located in the Lille region of northern France. He is affiliated with the College of Engineering, contributing to academic and research initiatives in software engineering and robotics. His work bridges academia and industry through his active involvement in both teaching and entrepreneurial ventures. Research Interests: His research spans two major domains: Software Engineering (SE) and Artificial Intelligence (AI) for mobile and autonomous robots. In SE, he investigates software architectures, dynamic reflective languages (especially Pharo and JavaScript via PharoJS), and tools enabling modular and agile development. In AI, his focus lies on coordination and cooperation mechanisms in robotic fleets, including communication models and emergent or predefined organizational structures in multi-agent robotic systems. His entrepreneurial endeavors include co-founding nootrix , a startup that develops PLC3000 , a SaaS platform dedicated to teaching PLC programming and factory automation, reflecting his commitment to practical technology education. He has supervised PhD students, post-doctoral fellows, and research engineers, demonstrating an active role in mentoring and collaborative research. His scholarly output can be explored via his Google Scholar profile. Professional Engagement: Noury shares insights through his blog (with RSS feed) and is active on LinkedIn , maintaining a public presence in technology and robotics communities. Advising & Collaboration: He has mentored several early-career researchers, including doctoral candidates (as co-advisor), post-doctoral fellows, and research engineers, contributing to a vibrant research team focused on robotics and software innovation. Labs & Teams: While specific lab names are not mentioned, his research activities suggest leadership or active participation in a robotics and software engineering research group at IMT Nord Europe, integrating both academic inquiry and practical tool development.
François Suro is a Lecturer at the University Institute of Technology, Valence within Grenoble Alpes University. He is affiliated with the LCIS laboratory and conducts research as part of the Co4Sys team. He earned his PhD in Computer Science from the University of Montpellier in 2020, focusing on epigenetic learning in multi-agent systems. Research Focus: His work centers on developmental approaches to artificial intelligence, with three primary domains: Progressive structuring of agent behaviors through hierarchical architectures (MIND framework) Acquisition and grounding of symbolic representations in embodied systems Emergence mechanisms for collective behaviors in agent societies Key application areas include robotics, social simulations, and cognitive modeling. Publication Trends: Recent works (2019-2021) demonstrate consistent exploration of hierarchical control architectures for autonomous agents, progressive learning methodologies, and collective behavior emergence in multi-agent environments. Dominant themes include developmental robotics frameworks, modular skill composition, and agent-based social simulations using platforms like NetLogo. Laboratory Context: As part of the LCIS laboratory's Co4Sys research team, he contributes to projects involving intelligent systems design and multi-agent coordination frameworks.
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.
Laurent ALFANDARI is a Full Professor at ESSEC Business School, specializing in Operations Research and Decision Analytics within the Information Systems, Decision Sciences and Statistics (IDS) Department. He has held key academic roles including Academic Co-Director of the ESSEC-CentraleSupélec Master in Data Sciences & Business Analytics (2019–2023) and Coordinator of the Operations & Data Analytics PhD concentration (2018–2021). His research focuses on optimization techniques applied to supply chains, logistics, healthcare, and disaster preparedness. He has authored over 50 journal articles in top venues like European Journal of Operational Research and Transportation Science. Education : - Doctorate in Operations Research (Université Paris Dauphine-PSL, 1999) - Master of Research in Management Science (Université Paris Dauphine-PSL, 1995) - M.Sc in Management (ESSEC Business School, 1993) - Bachelor in Mathematics & Social Sciences (Université Paris Dauphine-PSL, 1990) Research Interests : His work addresses complex optimization challenges in urban logistics, healthcare networks, and disaster response. Notable contributions include freight-on-transit systems, autonomous robot delivery, and pandemic intervention sequencing. He emphasizes practical solutions for real-world problems through mixed-integer programming and robust optimization frameworks. Teaching & Mentoring : Teaches Decision Analytics and Operations Research across ESSEC programs (Grande École, Executive MBA, PhD). Supervised 14 PhD theses, including recent works on sustainable last-mile deliveries and healthcare analytics. Awards & Activities : 2020 ESSEC Top 4 Teaching Award, Vice-President of ROADEF (2012–2015), and leader in industrial collaborations with SNCF and Aid-Impact. Active in organizing academic conferences and serves as a journal reviewer for Annals of Operations Research and others. Labs & Collaborations : Member of LIPN (Sorbonne Université) and LAMSADE (Paris Dauphine). Consults for organizations like Babcock-Wanson and contributes to public-sector projects like EDF's ROADEF challenge.
Fabrice Duval is a Researcher-Lecturer and Head of the Technical Research and Transfer Platform at CESI. He holds a Habilitation to supervise research from Rouen University (2016) and a PhD in Electrical Engineering from Université Paris-Saclay (2007). His research focuses on Industrial Performance Optimization, Electromagnetic Compatibility (EMC), and robotics-driven manufacturing systems. He leads the 'Engineering and Numerical Tools' research team and manages the CESI FabLab. His educational activities include teaching Electromagnetism, Electricity, and Embedded Systems to engineering students (1st/2nd years and masters). He has supervised numerous PhD theses, including those on EMC in electric vehicles, motor impedance modeling, and PEEC-based EMI analysis. His work emphasizes practical applications, such as the CoRoT project (2016-2021) improving flexible manufacturing systems with autonomous/collaborative robots. Key research themes include robotics task allocation (e.g., auction-based optimization), digital twin integration for resilient systems, and synthetic data for industrial object detection. His publications span peer-reviewed journals and conferences, addressing topics like magnetic shielding effectiveness in automotive applications and modular mobile manipulator coordination. Awards: While no specific honors are listed, his extensive supervision record and participation in high-impact projects reflect his academic standing. He actively organizes scientific events and contributes to industry-research partnerships. Lab involvement: As FabLab manager, he bridges academic research with hands-on innovation, fostering experimental prototyping in electromechanical systems and smart manufacturing technologies.
Simon Thevenin is an Assistant Professor in the Automation, Production, and Computer Sciences Department at IMT Atlantique in France since 2018. He holds a Ph.D. from the University of Geneva (2015) and previously worked as a Postdoctoral researcher at HEC Montreal and an Algorithm Expert at Quintiq. His research focuses on optimization methods for production management, including scheduling, planning, and manufacturing line design. He leads projects such as the EU-funded ASSISTANT (2020-2023), ALICIA (2023-2025), and ACCURATE (2023-2026), advancing AI-driven solutions for sustainable manufacturing and supply chain resilience. His work integrates machine learning, robust optimization, and digital twin technologies to enhance production systems' adaptability and efficiency. Education: Ph.D. in Production Systems Scheduling, University of Geneva (2015) Teaching/Research Assistant, University of Geneva (2010-2015) Research Interests: His research emphasizes optimization under uncertainty, reconfigurable manufacturing systems, and AI applications in production. He explores topics like lot-sizing models, equipment lifecycle management, and circular manufacturing ecosystems. Grants/Projects: ASSISTANT (EU-funded, 2020-2023): AI for production digital twins ALICIA (EU-funded, 2023-2025): Circular production resource ecosystems ACCURATE (EU-funded, 2023-2026): Supply chain resilience against disruptions Labs/Teams: Part of the LS2N research lab (Modelis team) at IMT Atlantique, specializing in logistics and industrial optimization.
Sylvain Durand Chamontin serves as an Associate Professor at INSA Strasbourg, affiliated with the ICube research laboratory (UMR 7357) and the AVR (Automation, Vision, Robotics) team. His teaching encompasses advanced automation (anti-windup, Smith predictor, LQ control), embedded systems/IoT, motorization/axis control, linear automation (state feedback, observers), and sequential automation (GRAFCET, GEMMA) for electrical engineering, mechatronics, and mechanical engineering students across 2nd–5th year programs. His research centers on frugal design and control of embedded cyber-physical/robotic systems under resource constraints, with a dedicated focus on non-periodic sampling and event-driven techniques . Key domains include event-driven control architectures, dynamic vision sensor-based visual servoing, aerial robotics (UAVs/aerial manipulators), and swarm robotics. This work systematically reduces computational load, communication overhead, and energy consumption while maintaining robust performance in resource-limited environments—critical for embedded implementations in drones and cyber-physical systems. Analysis of Durand's 15 most recent publications (2022–2025) reveals a dominant trend in event-driven control for robotics, increasingly integrating machine learning for adaptive tuning. His work targets practical applications in aerial robotics, including UAV stabilization under ground effects, elastic-suspension aerial manipulation, and event-based visual servoing. A strong emphasis on frugality permeates techniques like non-periodic sampling and resource-aware control strategies, directly addressing hardware limitations in embedded platforms. Durand mentors award-winning PhD students including M. Pivert (Best Student Paper Award, IFAC Robotics 2025), T. Paul (i-PhD Innovation Contest 2022), and A. Yiğit (Best PhD Award in French Robotics 2021). He leads multiple ANR-funded projects: e-VISER (event-driven visual control, 2018–2021), DexterWide (cable robots, 2015–2018), and current initiatives eSWARM (modular UAVs, 2023–2025), muteSWARM (acoustic swarm control, 2023–2027), STRAD (street art drone, 2022–2026), TIR4sTREEt (urban micro-climatology, 2022–2026), and dark-NAV (GPS-denied navigation, 2021–2025). Within ICube's AVR team, Durand drives laboratory development of the dextAIR robot (omnidirectional aerial manipulator with elastic suspension) and embedded control systems for cable-driven parallel robots and swarm robotics. His experimental work emphasizes real-time implementation, energy efficiency, and frugal engineering principles—translating theoretical event-driven control into hardware solutions for resource-constrained robotic applications.
Benoit Piranda is an Associate Professor of Computer Science at the University of Franche-Comté , affiliated with the FEMTO-ST Institute and its Complex Networks Team (DISC/OMNI) . He leads the development of VisibleSim , a parallel behavioral simulator for modular robots. University: University of Franche-Comté Institute: FEMTO-ST Team: DISC/OMNI Role: Researcher & Software Developer Research Focus: Distributed algorithms for modular robots, programmable matter, physical simulations, and parallel execution environments. His work spans self-reconfiguration, communication protocols, and efficient scene encoding for large-scale robotic systems. Article Trends: Recent publications highlight advancements in 2D/3D lattice modular robot algorithms Porous structure reconfiguration Time synchronization protocols VisibleSim simulation framework Multi-scale distributed displays Security protocols for programmable matter Conference Involvement: Active in program committees for DARS, IEEE ATC, IROS, and AINA. Former Publicity Chair positions.
