Emilie Carretier is a Professor at Aix-Marseille University (AMU) , affiliated with the Procédés Membranaires research team. Her work focuses on membrane separation technologies, particularly for industrial applications in pharmaceuticals, water treatment, and nuclear waste management. Research Interests : Membrane processes (pervaporation, reverse osmosis), solvent regeneration, radioactive effluent treatment, catalyst recovery, and industrial sustainability. Publications highlight advancements in ceramic membranes, VOC removal, and membrane aging studies, with applications in pharmaceuticals, microelectronics, and nuclear industries. Laboratory : Active within the M2P2 research center, specializing in membrane process innovation for complex industrial matrices.
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.
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.
Vishnu S Nair serves as Assistant Professor (Grade I) in the School of Earth, Environmental and Sustainability Sciences at IISER Thiruvananthapuram since January 2024, following postdoctoral positions at IRD-France (2022-2023) and UC Berkeley (2019-2021). His research bridges tropical meteorology and climate science with practical applications for monsoon forecasting and climate adaptation. Education PhD in Meteorology & Oceanography, ESSO-INCOIS/Andhra University (2011-2017) Dr. Nair's research centers on monsoon low-pressure systems, investigating their historical variability, climate change impacts, and connections to extreme rainfall events. He develops advanced tracking algorithms and dynamical downscaling techniques to improve climate projections for vulnerable regions like South Asia and Pacific Islands. His work integrates observational analysis, climate modeling, and real-time forecasting systems to address critical questions about monsoon dynamics under global warming. His 14 publications (2014-2023) reveal consistent focus on monsoon system behavior, with recent work emphasizing future projections of low-pressure systems and observed increases in extreme rainfall rates. Key methodologies include high-resolution modeling, global dataset creation, and teleconnection analysis between monsoons and phenomena like ENSO and IOD. Scientific Recognition Gold Medal for Best PhD Thesis, Andhra University (2018) Junior Research Fellowship with Lectureship, CSIR-UGC (2011) CLIPSSA Postdoctoral Fellowship at IRD-France (2022-2023) Monsoon Mission Postdoctoral Fellowship at UC Berkeley (2019-2021) Dr. Nair actively recruits PhD candidates (requiring CSIR-JRF/GATE fellowships) and offers winter/summer internships in tropical meteorology. His research is supported by international projects including CLIPSSA for Pacific Island climate adaptation and India's Monsoon Mission for forecasting improvements. He contributes to global monsoon datasets used by meteorologists worldwide and serves as referee for leading journals like Geophysical Research Letters . He leads the Monsoon Dynamics Research Group at IISER-TVM, collaborating with institutions including Météo-France, UC Berkeley, and Indian climate research centers. Current initiatives focus on dynamical downscaling for island-scale climate projections and real-time tracking systems for monsoon low-pressure systems.
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.
Samir Ouchani is a Research Director at the CESI LINEACT laboratory (Aix-en-Provence, France), affiliated with the CESI Engineering School. He holds a PhD in Computer Science from Concordia University (2013) and an HDR (Accreditation to Supervise Research) from CNAM Paris (2022). His research focuses on securing cyber-physical systems (CPS) through formal methods, blockchain, and AI-driven approaches. Key roles include leading projects on resilient CPS architectures, IoT security, and federated learning in industrial contexts. Education: 2022: HDR in Security and Reliability of Smart CPS (CNAM Paris) 2013: PhD in Computer Science (Concordia University, Montreal) 2006: Master in Computer Science (Lorraine University, France) 1997: Engineering Degree in Computer Science (Djillali Liabess University, Algeria) Research Interests: His work emphasizes secure CPS design, including cryptographic protocols for IoT, formal verification frameworks, and AI applications for intrusion detection. He explores blockchain for smart cities, federated learning in distributed systems, and resilience engineering for autonomous vehicles. Recent projects include developing PUF-based authentication protocols and digital twin architectures for resource-constrained systems. Advising & Collaborations: Supervised PhD theses on IoT security (Fahem Zerrouki), smart city formal verification (Walid Miloud Dahmane), and federated learning in industrial CPS (Souhila Bedra Guendouzi). Collaborates with institutions like Blida University (Algeria) and HESAM University. Active in conferences such as CRISIS, ICFNDS, and IEEE WETICE. Labs & Teams: Leads the Engineering and Numerical Tools research team at CESI LINEACT, focusing on model-based design, CPS simulation, and cybersecurity tool development. Engaged in EU-funded projects on Industry 4.0 and smart infrastructure security.
Jean-Marie Bonnin is a Researcher at IMT Atlantique , affiliated with the Network Systems, Cyber Security and Digital Law department. His work spans autonomous industrial vehicles, vehicular networks, and cooperative systems, with a focus on energy management, task allocation, and safety protocols. IMT Atlantique, Rennes Campus Research in Industry 4.0 and Smart Mobility Research Interests : Autonomous Industrial Vehicle Fleets Fuzzy Logic for Multi-Agent Systems V2X Communication Protocols Scientific Contributions include: Modeling energy consumption in extreme-edge IoT nodes Decentralized task allocation for autonomous vehicles Collision avoidance in industrial environments
Benoît Lemaire is a permanent Lecturer at the University of Grenoble Alpes, affiliated with the Laboratoire de Psychologie et NeuroCognition (LPNC) and the CoMMet team (Consciousness, Memory and MetaCognition). His academic career spans computational cognitive modeling, with a focus on working memory, eye movement research, and educational technology applications. PhD in Computer Science/AI, Université Paris-Sud (1989-1992) Postdoctoral Research: University of Pittsburgh (1993), Swedish Institute of Computer Science (1994) Academic Roles: Maître de conférences (1996-), transitioning through Laboratoire des Sciences de l'Éducation (1994-1996), Laboratoire Leibniz (2004-2006), TIMC (2006-2010), and LPNC (2010-). Lemaire’s research integrates computational modeling with empirical studies across multiple domains: Working Memory : Time-based decay, interference effects, semantic compression, and attentional refreshing mechanisms. Eye Movements : Information search in texts, reading strategies, and visual-semantic integration. Educational Applications : Text assessment, metaphor comprehension, and adaptive learning systems. Inductive Learning : MDL-based models for concept learning and lexical knowledge acquisition. His recent publications (2021–2025) emphasize computational models of mental arithmetic, semantic knowledge impacts on memory, and similarity-based compression techniques. All work aligns with cognitive science and AI methodologies. Current affiliations include: Laboratoire de Psychologie et NeuroCognition (LPNC) – 2010- CoMMet team (Consciousness, Memory and MetaCognition) University of Grenoble Alpes – Permanent Lecturer
Toufik AZIB is a Full Professor and scientific coordinator of the ECMS (Energy and Conception of Mechatronic Systems) research theme at ESTACA Engineering School in France. He leads a team of 6 teacher-researchers and 13 PhD students, focusing on optimal design of power electronics and energy management for hybrid power systems. His work bridges academic research and industrial applications in sustainable mobility, with strong collaborations across Europe and Algeria. Dr. AZIB received his Electrotechnical Engineering Diploma from the University of Setif, Algeria in 2006, followed by an M.Sc. in Electrical Engineering from ENSEM-INPL, France in 2007. He earned his Ph.D. in electrical engineering from the University of Paris South XI in 2010 and completed his HDR (Habilitation à Diriger des Recherches) from the University of Paris Saclay in 2021. His academic journey reflects a strong foundation in both theoretical and applied electrical engineering. His research focuses on the modeling, control, and optimal design of embedded energy systems under multi-physical constraints (electrical, thermal, electromagnetic compatibility, volume, reliability). He specializes in energy management strategies for hybrid systems combining fuel cells, batteries, and ultracapacitors, with applications in electric vehicles and the 'more electric aircraft.' His work integrates numerical and experimental approaches to develop methodologies for pre-dimensioning and real-time energy management, addressing challenges in sustainable transportation. Analysis of Dr. AZIB's recent publications reveals a strong trend toward multidisciplinary design optimization for automotive applications, particularly electronic throttle systems. His research increasingly incorporates knowledge management techniques and addresses reliability considerations in hybrid power source design. There's a clear progression from fundamental energy management strategies to sophisticated eco-driving solutions for electric vehicles, reflecting the evolving demands of sustainable mobility. Best Paper Award for 'Structure and Control Strategy for a Parallel Hybrid Fuel Cell/Supercapacitors Power Source' at IEEE VPPC'09 Dr. AZIB has supervised numerous PhD and Master's students across multiple institutions in France, Algeria, and Colombia. He leads significant research projects including MIMe (Module d'Intégration et de simulation Mécatronique), ECOS Nord (Eco-driving strategies for electric motorcycle), and AmCoAIR (improving air quality in vehicle cabins), securing funding from national and international sources. His work demonstrates strong industry collaboration with partners like Valeo, PSA, and Renault. As experimental platforms coordinator since 2012, Dr. AZIB oversees 10 specialized experimental facilities at ESTACA's S2ET-Paris Saclay research pole, including those for autonomous electric vehicles, drones, electric machines, and power modulators. His team regularly develops proof-of-concept demonstrators to validate research findings, such as the Formula Student electric vehicle and the 'Electric Appeal' streamliner project, demonstrating practical applications of their theoretical work.
Overview ASSILA Ahlem is a Researcher-Lecturer at CESI, specializing in Human-Machine Interaction (HMI), Augmented Reality (AR), and Virtual Reality (VR). She holds a PhD in Computer Science from Université de Valenciennes (2016) and a postdoctoral position at Institut Image ARTS ET METIERS PARISTECH (2017). Her research focuses on usability evaluation, digital twin technology, and BIM-integrated XR systems. She has supervised multiple engineering and master’s projects, including AR application development for network management. Research Contributions Developed frameworks for integrating subjective/objective usability metrics using ISO standards Proposed maturity models for BIM-based AR/VR systems Explored digital twin applications in manufacturing and construction industries Education & Responsibilities Teaches computer science at all engineering levels (L1-M2) at CESI Reims, including algorithmics, HMI design, and project-based learning. Served as pilot for engineering program cycles (2017–2020). Active in organizing international conferences (e.g., HCI 2020, Flexible Automation 2018) and peer review for journals like IJISE and IEEE VR. Awards & Recognition No specific awards listed, but recognized for contributions to HCI and industry-relevant research. Advising & Grants Supervised over 10 student projects including PFEs and internships. Actively participates in jury panels for engineering thesis defenses and academic promotions across multiple institutions. Labs & Collaborations Member of the CESI Chair for Industry and Services of Tomorrow, focusing on technology integration in construction and manufacturing sectors.
Zeina ELRAWASHDEH is a Researcher Lecturer at the Institut Catholique d'Arts et Métiers (ICAM), based at the Grand Paris Sud campus. Her research focuses on Measurements and Controls, with a particular emphasis on fiber-optic sensors, multi-agent systems, and IoT integration for smart infrastructure. She collaborates with prestigious research laboratories globally to develop innovative solutions in energy optimization, smart cities, and precision engineering. Her expertise spans applied research in fiber-optic displacement sensors, algorithm optimization for sensor performance, and user-centric building automation systems. Zeina’s work bridges theoretical advancements with practical applications in manufacturing, energy, and urban systems. She actively contributes to international academic discourse through peer-reviewed publications and participates in ICAM’s strong industry partnerships for applied research outcomes. Zeina’s research portfolio demonstrates a trajectory toward integrating AI and IoT with traditional engineering challenges, addressing technical gaps in sensor networks, multi-agent coordination, and precision machining. Her recent work highlights advancements in smart city infrastructure and energy-efficient building systems. While no awards are explicitly mentioned, her involvement in ICAM’s research initiatives underscores her commitment to impactful, industry-relevant science. Collaborations with global companies and academic institutions position her at the forefront of applied engineering research.
Denis Duhamel is a Professor and researcher at the Navier Laboratory, affiliated with École des Ponts ParisTech. He teaches mechanics courses at École nationale des ponts et chaussées and previously lectured at École Polytechnique. He earned his doctorate from École des Ponts ParisTech (1994) and research accreditation from University of Marne la Vallée (1998). His research focuses on structural acoustics, railway dynamics, tire-road noise, and numerical modeling of vibrations using Wave Finite Element (WFE) methods. Key areas include railway track dynamics, vibration control, and acoustic barrier performance. Notable projects involve dynamic analysis of periodic structures like railway tracks and metamaterials. Recent publications (2020–2025) emphasize wave-based methods for periodic structures, nonlinear foundation modeling, and in-situ measurements of acoustic barriers. His work bridges theoretical models with practical applications in transportation and structural engineering. Lab affiliations include the Navier Laboratory, a leading center for mechanics and materials research. He collaborates on projects like DEUFRABASE for pavement noise evaluation and ODSurf for optimized road surface design.
Bruno Vallespir is a Professor at Universite de Bordeaux, affiliated with the Production Engineering research group and MEI team. His work focuses on lean manufacturing, industry 4.0 integration, and enterprise interoperability using simulation frameworks. Key research themes: Lean techniques evaluation Co-simulation for manufacturing systems Organizational interoperability Safe work activity design His recent publications address: Combining lean methods with Industry 4.0 technologies Human-machine interaction in production environments Verification of collaborative processes Performance metrics for dynamic industrial contexts Collaborations include institutions like IMS Bordeaux , INCOSE , and industrial partners such as STMicroelectronics , Thales , and Stellantis .
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.
