Laurent Tapie is a Senior Lecturer at Paris Descartes University with a focus on Biomedical Engineering, Mechanical Engineering, and CAD/CAM . As Deputy Director of the URB2i research unit and manager of the PlatiNum platform , he coordinates the 3d4care.org consortium . His academic background includes a Doctorate in Mechanical Engineering from École Normale Supérieure de Cachan and authorization to direct research (HDR) from Université Paris 13. Research Interests: Mechanical Engineering, Biomedical Engineering, Medical Devices, CAD/CAM, Shaping of Biomaterials Theses Supervised: 3D evaluation of dento-prosthetic joints, impact of CAD/CAM on dental prosthesis integrity, and metrological evaluations of prostheses. Publications: His work spans dental CAD/CAM systems, surface integrity of prostheses, additive manufacturing, and 3D printing applications during the COVID-19 pandemic . Recent articles focus on data dispersion in CAD/CAM chains, tool-material influence on roughness, and numerical workflow standardization . Scientific Award: Prix du comité scientifique de la session recherche (2019). Projects: Currently leads initiatives like ProGéoMéca (Labex LaSIPS), Bio-Dents (CNRS Biomimicry), and additive process development for multi-material dental aligners .
National Institute of Science and Technology (INSA)France
Thomas Grenier is an Associate Professor in the Department of Electrical Engineering at INSA Lyon and a member of the CREATIS laboratory (CNRS UMR 5220, INSERM U1294). He obtained his HDR (Habilitation à Diriger des Recherches) in 2023 and his Ph.D. in Image Processing from INSA Lyon in 2005. His research focuses on medical image segmentation, clustering, and filtering using feature space, scale-space, and deep learning approaches. Doctoral School: EEA (Electronics, Energy, and Automatics) Research Affiliation: CREATIS Lab (CNRS/INSERM/INSA Lyon/Université Lyon 1/Université Jean Monnet Saint-Etienne) He has contributed to 20 papers and co-supervised 5 PhD students, including Léo Dumortier and Florent Guépin. Grenier leads the annual Deep Learning for Medical Imaging (DLMI) school, which he co-founded, and has organized five editions across Lyon and Montreal since 2019. The school emphasizes practical deep learning applications in medical imaging for participants of all expertise levels. His work spans interdisciplinary domains such as medical imaging , deep learning , and image processing , with recent publications on generative AI for MRI synthesis, explainable networks, and segmentation of neurological pathologies in preclinical models. He manages pedagogical platforms, coordinates LabEx PRIMES project activities, and oversees lab room infrastructure for 200 hours/year across 10 training programs. Grenier also leads the MUSIC transversal project on Multiple Sclerosis since 2019.
Christine Di Martinelly is an Associate Professor in Operations Management at IÉSEG School of Management. She holds two PhDs in Economic and Management Sciences from Louvain School of Management and Applied Sciences from INSA Lyon. Her research focuses on operations management, healthcare systems, supply chain optimization, and resource allocation. Di Martinelly's extensive publication record addresses operational challenges in healthcare, including surgical scheduling, inventory management, and resource allocation. Her work employs mathematical modeling, optimization algorithms, and multicriteria decision analysis to improve efficiency in healthcare delivery systems. She has served as Academic Director at IÉSEG since 2014 and has professional experience as a consultant at Arthur Andersen earlier in her career.
Stephane Cotin is a Research Director at Inria and leader of the MIMESIS team, specializing in real-time physics-based medical simulations. His work focuses on surgical training, planning, and image-guided therapy, with over 200 scientific articles and the development of the open-source SOFA framework. He co-founded InSimo, Twinical, and EVE, and previously held roles at Harvard Medical School and Mitsubishi Electric Research Lab. Cotin’s research bridges imaging, robotics, and medicine to improve healthcare outcomes, emphasizing patient-specific biophysical modeling and real-time computation. His awards include the Academy of Sciences Award (2018) and Dirk Bartz Medical Prize (2015). He has advised numerous PhD students and led projects like MediTwin and PREMYOM, advancing digital twin technologies for precision medicine.
Chao Liu is a Research Scientist at CNRS (French National Center for Scientific Research) since 2008, affiliated with the DEXTER team and the Department of Robotics, LIRMM at University of Montpellier, France. He earned his Ph.D. in Electrical & Electronic Engineering from Nanyang Technological University, Singapore (2006). Current research focuses on surgical robotics , haptics , teleoperation , and nonlinear control theory with applications in computer vision. His work addresses challenges in robotic-assisted telesurgery, including: Stable and transparent human-robot interaction through wave variable compensators and passivity filters Physiological motion compensation using spatio-temporal LSTM and dual Kalman filters EMG-based motion recognition for surgical skill assessment 3D soft-tissue reconstruction with stereo-endoscopes and deep learning Dr. Liu leads European and French projects like: TS2RT (CNRS-funded): Safer teleoperation with motion compensation ROBACUS (ANR-funded): Needle positioning with MPC control HaTUMoCo (CNRS-funded): Haptic teleoperation with uncertainty handling ARAKNES (EU-funded): Microrobotic systems for endoluminal surgery Scientific honors include Senior Member of IEEE and Member of Sigma Xi . He supervises Ph.D. and Master's students working on topics such as concentric tube robot optimization, haptic teleoperation, and EMG-based force estimation. Dr. Liu serves on IEEE Technical Committees for Telerobotics and Haptics , and as Technical Editor of IEEE/ASME Transactions on Mechatronics.
Dr. Imen NOUIRA is a Full Professor in the Supply Chain Management & Information Systems Academic Area at Rennes School of Business (since 2023). She holds a Ph.D. from Grenoble INP (2013) and has extensive academic experience, progressing from Assistant Professor (2012-2019) to Associate Professor (2019-2023). Her research focuses on supply chain optimization under environmental considerations, carbon emissions modeling, and pandemic logistics. She has published in top journals like European Journal of Operational Research and International Journal of Production Economics. Key research interests include: Environmental Sustainability : Green supply chain design, carbon taxation strategies, and eco-friendly product development Healthcare Supply Chains : Pandemic medical product distribution and crisis management Operations Research : Inventory optimization, lead time coordination, and stochastic modeling Her work has been recognized with awards such as the 2017 2nd Best Student Paper Award at IESM. She actively contributes to international conferences and collaborates with industry partners on projects like olive oil supply chain design and carbon tax policy analysis. Rennes School of Business affiliations include roles in the: Green, Digital & Demand-Driven Supply Chain Management (G3D) research center Agribusiness, Sustainable Development, and CSR initiatives
Philippe Moireau is a Full Professor in the Department of Applied Mathematics at École Polytechnique, where he is also affiliated with the Center for Applied Mathematics (CMAP). He serves as the head of the Inria Project-Team MΞDISIM (Mathematical and Mechanical Modeling with Data Interaction for Simulation in Medicine) and holds the distinguished position of Ingénieur Général of The Corps des Mines. His primary research focuses on inverse problems and data assimilation for partial differential equation models, with particular emphasis on: Observer-based methods from optimal control perspectives Stabilization approaches for evolution equations Numerical analysis of time-dependent control problems Digital twin applications in cardiovascular medicine Professor Moireau's publication portfolio demonstrates consistent focus on mathematical methods for physical systems, with recurring themes in: Data assimilation techniques for PDE-based models Numerical stabilization and discretization methods Cardiovascular biomechanics and hemodynamics Stochastic modeling of biological systems Epidemiological forecasting and control He leads the ANANKΞ project-team at Inria focused on Analysis And Numerics of physical-Knowledge-based Estimation. His educational contributions include lectures on data assimilation theory at CEMRACS and courses on mathematical modeling in cardiac biomechanics at Institut Polytechnique de Paris.
Khalifa Aguir is a Professor at Aix-Marseille University, affiliated with the Department of Detection, Radiation and Reliability (DETECT) and the Microsensor Instrumentation (MCI) Team. His research focuses on gas sensing technologies , particularly metal oxide semiconductors , nanomaterials , and thin films for environmental and biomedical applications.
Olivier ALLIX is a Professor at the Laboratoire de Mécanique et Technologie (LMT) at École Normale Supérieure de Cachan (ENS-Cachan). His research focuses on computational mechanics, including multiscale modeling of composite materials, structural failure analysis, and non-intrusive coupling strategies. He has held leadership roles such as Head of LMT-Cachan and Vice-president of the International Association for Computational Mechanics (IACM). Expertise: Computational structural mechanics, material failure, inverse problems, and multiscale approaches. Editorial Roles: Associate editor of multiple journals including Computational Mechanics and Computer Methods in Applied Mechanics and Engineering . Awards: IACM Fellow, Euromech Fellow, and recipient of the Gay-Lussac Humboldt Prize (2019). His work integrates experimental mechanics with computational methods, emphasizing big data applications and model validation. He has organized major conferences like the World Congress on Computational Mechanics and co-led international research initiatives such as the IRTG ‘Virtual Material and Structures’ with Hannover University. Teaching includes advanced courses on structural dynamics, composite materials, and computational mechanics at the Master’s level. His research group collaborates with industries like Safran, IFPEN, and DGA on projects involving fatigue analysis, mooring systems, and composite testing.
Guillaume DELATOUR is an Associate Professor in Risk and Crisis Management at Université de Technologie de Troyes (UTT), specializing in organizational resilience and security dynamics. He leads UTT's InSyTE laboratory's crisis/resilience/security research axis and coordinates the PRESAGES crisis simulation platform. His academic roles include directing the IMSGA Master's program in Global Security Engineering and co-developing executive certificates like DSRT (Ministry of Interior collaboration) and AMCSS (ENSP partnership). Research focuses on crisis cell coordination, community resilience post-disasters (e.g., Storm Alex studies), and temporal dynamics in crisis management. He has coordinated major projects including ANR-funded INPLIC (2018-2021) and regional initiatives on rural crisis preparedness. His educational contributions span crisis simulation pedagogy and integrating citizen participation in disaster response strategies. Published extensively in crisis management, his 2023 work on Storm Alex solidarity mechanisms and 2024 papers on crisis cell coordination exemplify his focus on real-world operational challenges. Advises PhD students Gaëtan Chevalier and Aymée Nakasato, exploring crisis simulation frameworks and collective risk behaviors. Education: PhD (2011-2015) on decision-making in high-risk environments, Research Engineer at UTT (2015-2017), UN research stint (2010). Grants: ANR, IHEMI/FIESP, regional funding for RPM project (2015-2016). Labs/Teams: InSyTE Lab, Chaire Gestion des Crises, Chaire Sécurité Globale.
Frédéric Keck is a Research Fellow at the French National Centre for Scientific Research (CNRS) and heads the Social Anthropology Laboratory (Laboratoire d'Anthropologie Sociale, LAS) at the École des hautes études en sciences sociales (EHESS). He specializes in medical anthropology, focusing on health crises, zoonoses, and biosecurity. His work bridges philosophy, epidemiology, and ecological studies, with notable research on avian flu in Hong Kong and pandemic preparedness. Education: PhD in Philosophy (2003) from University of Lille-III DEA in Philosophy (1999) from University of Paris X-Nanterre Aggregation in Philosophy (1997) Exchange at UC Berkeley (1998-1999) Research Themes: Biopolitics, food risks, scientific networks, ecological disasters, conservation, and zoonotic diseases. His interdisciplinary approach spans anthropology, epidemiology, and policy analysis, with a focus on how scientific expertise shapes global health governance. Publications: Over 20 books and articles, including A World with Flu (2010), Pandemic Sentinels (2020), and works on avian influenza's societal impacts. His writing emphasizes the interplay between human and animal health, surveillance systems, and cultural perceptions of risk. Awards: CNRS Bronze Medal (2011), Fyssen Foundation Grant (2007), and membership in the Canadian Institute for Advanced Research (2015). Roles: Directed the Musée du Quai Branly's research department (2014–2018) and currently leads LAS. Engaged in global health initiatives and collaborative projects on veterinary anthropology and disaster preparedness. Labs/Teams: LAS (CNRS UMR 7130), collaborating with international networks on biosecurity, zoonoses, and environmental anthropology.
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.
Alain Oustaloup is a Professor in the AUTOMATIC CONTROL research group at Université de Bordeaux , leading the CRONE team. His work focuses on fractional calculus , system identification , and control theory , with applications spanning thermal systems , epidemiology , and automotive engineering . Expertise : Fractional Order Modeling, CRONE Control, Thermal Diffusion Analysis Key Collaborations : Université de Lorraine, CNRS, STMicroelectronics His research includes fractional differentiation models for continuous-time system identification, non-integer power models for viral spread (e.g., COVID-19 ), and infinite state approaches for complex system representation. Recent publications emphasize thermal modeling and fractional prefilters for MIMO systems. Applications of his work extend to automotive suspensions (CRONE method), battery diagnostics , and medical device modeling . Collaborations with institutions like CRAN (Nancy) and IMS-Bordeaux highlight his interdisciplinary impact.
Vinkle Srivastav is a Research Scientist (Chargé de recherche R&D) at the CAMMA group, a collaborative research team between IHU Strasbourg and the University of Strasbourg, where he focuses on advancing surgical data science through novel computer vision and machine learning approaches. His work bridges the gap between clinical practice and artificial intelligence, developing methods for surgical video analysis, 3D medical imaging, and surgical workflow understanding. Education PhD in Computer Science (2018-2021) from University of Strasbourg, France. Thesis: "Unsupervised Domain Adaptation Approaches for Person Localization in the Operating Rooms." Master of Science in Computer Science (2014-2017) from Indian Institute of Technology, Delhi, India. Thesis: "Computerized evaluation of neurosurgery skills using image processing and computer vision techniques." Bachelor of Technology in Electronics and Communication (2007-2011) from Punjab Technical University, Jalandhar, India. Research Interests Vinkle's research spans surgical data science, with particular focus on multi-modal learning approaches for surgical computer vision. His work addresses fundamental challenges in medical AI including domain adaptation, self-supervised learning, and privacy preservation in clinical environments. He develops methods for 3D medical image analysis, multi-view human pose estimation in operating rooms, and surgical activity recognition. His recent work emphasizes multi-modal pretraining frameworks that leverage both visual and textual information to improve surgical workflow understanding. He also investigates scientific simulation techniques, particularly for therapeutic ultrasound applications, where physics-aware deep learning models can accelerate computational processes while maintaining accuracy. Publication Trends Vinkle's recent publications demonstrate a strong trajectory toward multi-modal surgical AI systems that integrate vision, language, and physics-based modeling. His work increasingly focuses on few-shot and zero-shot adaptation techniques to address the data scarcity problem in surgical AI. The publications reveal a progression from basic pose estimation to holistic surgical scene understanding, incorporating team communication analysis and surgical safety protocols. Scientific Awards IPCAI 2024 Best paper award (co-author) IPCAI 2019 Runner-up award in the bench-to-bedside category (co-author) Joint winner for the best paper award in the machine learning for CAI track, IPCAI 2025 Advising and Grants Vinkle actively mentors multiple PhD students and research interns at various levels, supervising thesis work on topics including large-scale multi-modality learning, holistic surgical scene analysis, and self-supervised video representation learning. He serves as Co-PI on two ITI-HealthTech projects: one focused on multi-modality learning for 3D medical imaging (2023), and another on physics-aware deep-learning approaches for therapeutic ultrasound simulation (2024). Laboratories and Teams Vinkle is a key member of the CAMMA research group at IHU Strasbourg, a collaborative team focused on computer-assisted medical modeling and analytics. He co-organizes the Surgical Data Science Summer School, an interdisciplinary program that brings together clinicians and computer scientists to develop AI-driven solutions with clinical impact. His work involves close collaboration with surgical teams at University Hospitals of Strasbourg and international partners including Johns Hopkins University and Technical University of Munich.
Jérémie DEQUIDT is a Researcher at Inria affiliated with Polytech Lille, University of Lille, serving as Thematic Group Facilitator for CO2 (Control and Scientific Computing) and Member of the Scientific Council. His offices are located at Inria Building A (Haute Borne) and Polytech Lille's Scientific City. His research spans soft robotics, simulation, control systems, and medical robotics. He develops modeling and simulation techniques for sensorimotor perception in soft robots and medical applications like prostate biopsy/brachytherapy using bio-inspired phantoms. His work integrates computer graphics, haptics, and deformable object robotics to advance medical interventions and robotic control systems. He supervises PhD students including Thomas Moupfouma (Sensorimotor perception in soft robotics through modeling and simulation) and Sizhe Tian (Simulation of needle insertion in bio-inspired active prostate phantom). As a core member of the DEFROST research team within CRIStAL laboratory (University of Lille/CNRS/Centrale Lille joint unit), he contributes to foundational research on deformable objects and robotics, with leadership roles in scientific governance and thematic coordination.
