Find Academic Supervisors

Iza MarfisiView profile

Professor

• Educational Technology
• Serious Games for Education
• Mobile Learning
• +5 more

Iza Marfisi is a Professor at the University of Le Mans where she became a University Professor in 2024 and was appointed Head of the IEIAH (Computer Environments for Human Learning) team in 2025. She works within the Claude Chappe Institute of Computer Science, focusing on developing educational technologies that empower teachers to create their own digital learning tools. Her research bridges computer science and educational theory to enhance teaching practices through accessible technology solutions, with particular emphasis on making advanced tools usable for non-technical educators. Marfisi's research spans Educational Technology, Serious Games for Education, Mobile Learning, and Extended Reality (XR), with a consistent focus on teacher-centered design. She develops "no-code" authoring tools enabling educators to create custom digital learning experiences deployable across various hardware platforms. Her work specifically targets situated learning with mobile devices, human-computer interactions for learning, and educational applications of mixed and extended reality. This approach democratizes access to advanced educational technologies by removing technical barriers for teachers. Analysis of her recent publications reveals a clear evolution from foundational mobile learning frameworks toward increasingly sophisticated integration of mixed reality and artificial intelligence in educational contexts. Her 2024-2025 work shows particular emphasis on generative AI for educational activity design, immersive pharmacology learning, and collaborative frameworks that connect multiple learning technologies. The publications consistently emphasize practical teacher needs, with many studies conducted in authentic educational settings rather than controlled laboratory environments. Marfisi actively supervises doctoral research across multiple dimensions of educational technology. Her current advisees explore artificial intelligence for mixed reality activity creation, mixed reality for professional training, free software approaches to serious games, and innovative interaction techniques for collaborative learning. Previous students have investigated mixed reality for fraction learning, educational game indexing systems, and mobile educational game design models. Her supervision portfolio demonstrates both depth in specific technical areas and breadth across the educational technology landscape. As Head of the IEIAH team at LIUM since 2025, Marfisi leads a research group focused on computer environments for human learning. She also serves on the Board of Directors for both the Serious Game Society and the IKIGAI association (Games for citizens), and was elected Deputy Director of Research at the Claude Chappe Institute of Computer Science since 2018. Her leadership extends to communications management for the IEIAH team and participation in the LIUM Laboratory Council (2022-2024), demonstrating significant institutional impact beyond her direct research contributions.

Oum El Kheir AktoufView profile

Professor

• Dependability
• Safety
• Security
• +5 more

Oum El Kheir Aktouf is a Professor in Computer Science at Grenoble Institute of Technology (Esisar Engineering School) and a member of the LCIS laboratory, France. She previously served as a Visiting Professor at San José State University, USA, during a sabbatical leave. Education : Master and PhD in Computer Science from Grenoble Institute of Technology Her research focuses on dependability, safety, and security of embedded and interconnected systems, including sensor-based applications and multi-agent architectures. She employs runtime testing, diagnosis, and monitoring approaches. Her work spans mobile application testing, fault diagnosis in RFID and wireless sensor networks, and security frameworks for autonomous systems. Recent publications highlight trends in Android security benchmarking , decentralized cryptography , and multi-agent resilience . She has participated in 12 funded national and international research projects and supervised courses in operating systems, real-time systems, distributed computing, and system dependability.

Massou LucView profile

Professor

• Digital Technology in Education
• Sociotechnical Analysis
• Information and Communication Sciences
• +2 more

Massou Luc is a full-time Professor at the University of Lorraine , affiliated with the Crem research unit and the Pixel team . He focuses on digital technology in education, particularly its sociotechnical analysis, professional practices, and educational applications. His work spans higher education, digital humanities, and international collaborations. Research Interests : Luc Massou investigates the use and non-use of digital tools in professional contexts, hybrid learning environments, open educational resources (OER), and digital inclusion. He emphasizes interdisciplinary frameworks, connecting information science, pedagogy, and sociotechnical systems. Recent Article Trends : 2025–2023: Hybrid learning models and typologies 2024–2022: Open education, African health communication websites 2021: Collaborative interfaces, language learning, and globalization impacts Scientific Roles : Co-manager of the Communication collection (University of Lorraine Publishing House, 2024–) Scientific advisor to the French Directorate for Higher Education (2020–) Co-founder of TiceMed and H2PTM conference series Projects : Contributor to CAP-CONTROVERSES (public engagement in environmental debates) Advisor in the FAM-WEST project on West Syndrome families Involved in European Erasmus+ and ANR-funded initiatives Teaching Leadership : Head of Master's in Audiovisual, Interactive Digital Media and Games (2021–2024) Responsible for work-study programs in digital media (2023–) Co-design of courses on digital project creation (2018–2024) Collaborations : Active in French and international research networks, including the GIS Éducation et Formation Grand Est and the European Communication Research and Education Association . He serves as an expert for journals like International Journal of Technologies in Higher Education and Terminal .

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

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

• Inventory Management
• Logistics
• Supply Chain Management
• +4 more

TRAN Minh Tam is an Assistant Professor at NEOMA Business School, France, specializing in Management Science and Operations Research. He holds a PhD in Industrial Engineering from INSA Lyon and dual Master’s degrees in Statistical and Financial Engineering, Data Science, and Mathematics of Insurance, Economics, and Finance from Paris Dauphine University, PSL University, and École Normale Supérieure de Paris. Research Focus: Digital transformation of supply chains, with emphasis on blockchain, AI, and data-driven decision-making Key Topics: Dual/multi-channel retailing, pricing strategies, stochastic demand modeling, omnichannel optimization Methodologies: Machine learning, operations research, game theory His work addresses cost reduction, service level improvements, and inventory accuracy challenges through quantitative models. Publications appear in journals like the International Journal of Production Economics and at conferences including INFORMS and ISIR. He previously conducted postdoctoral research at CentraleSupélec’s Industrial Engineering Laboratory and Future Cities Lab.

Sébastien FournierView profile

Researcher

• Aspect-Based Sentiment Analysis
• Multimodal Data Processing
• Information Retrieval
• +6 more

Sébastien Fournier is a researcher affiliated with the University of Aix-Marseille, focusing on natural language processing, multimodal data analysis, and agent-based systems. He has contributed to projects like ANR GUIDANCE, ADNvideo, CoPains, and PhysSocial, emphasizing dialogue-assisted information access, video fingerprinting, persuasive health agents, and psychophysiological foundations of social behavior. Research areas: Aspect-Based Sentiment Analysis, Contradiction Detection in Reviews, Multimodal Data, Recommendation Systems Projects: ANR GUIDANCE (Workpackage 3 Leader), ADNvideo (2014-2016), CoPains (2019-2022), PhysSocial (2018-2021) His work extends to evaluating interactions in serious crisis management games, with supervision of PhD students like Ismail Badache and Adrian-Gabriel Chifu. He collaborates with institutions including LIS, LSIS, and ILCB (Institute of Language, Communication and the Brain).

Bastien BerretView profile

Professor

• Neuroscience
• Biomechanics
• Robotics
• +5 more

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.

Anna KorbaView profile

Assistant Professor

• Machine Learning
• Bayesian Inference
• Sampling Methods
• +4 more

Anna Korba is an Assistant Professor at CREST-ENSAE Paris within the Statistics Department. She holds an ENSAE Engineering degree in Data Science and a Master's in Mathematics, Vision & Learning (MVA) from ENSAE Paris. Her career includes a Ph.D. in Machine Learning at Télécom ParisTech, followed by a postdoctoral position at UCL's Gatsby Unit. Her research focuses on sampling techniques, Bayesian inference, optimal transport, and generative modeling, with recent work on constrained sampling and fairness integration. She contributes to collaborative efforts at the intersection of machine learning, dynamical systems, and PDEs. Notably, she co-presented tutorials on Wasserstein gradient flows at ICML 2022. Her work addresses unsolved challenges in sampling efficiency and fairness constraints. She is actively involved in CREST research initiatives and academic mentorship.

Hachem KadriView profile

Professor

• Machine Learning
• Kernel Methods
• Functional Data Analysis
• +5 more

Hachem Kadri is a Professor of Artificial Intelligence in the Department of Computer Science at Aix-Marseille University and Head of the Data Science Department at LIS Lab since 2023. He was previously an Assistant Professor at the same institution from 2012 to 2019 and conducted postdoctoral research at INRIA Lille and LAGIS. He holds a PhD in Electrical Engineering from the National Engineering School of Tunis (2008) and completed his HDR (Habilitation) at Aix-Marseille University in 2019 on operator-valued kernel methods. His research spans machine learning with core expertise in kernel methods, functional data analysis, statistical learning theory, deep learning, and quantum machine learning, bridging theoretical foundations with applications in signal processing and quantum computing. Recent publications (2022-2024) demonstrate a strategic shift toward quantum machine learning and C*-algebraic frameworks, with significant contributions in implicit regularization for deep tensor factorization, quantum perceptron algorithms, and operator-theoretic kernel extensions. Key works appear in ICML, NeurIPS, and AISTATS, highlighting interdisciplinary innovation at the intersection of algebra, functional analysis, and ML. Professor Kadri leads the ANR Starting Grant QuantML (2019-2024) as Principal Investigator and co-led the Franco-Tunisian OPERA project (2019-2023). He was nominated to the National Universities Council (CNU) for 2024-2027 and elected Head of LIS Data Science Department in 2023, reflecting his leadership in French academia. As a core member of the QARMA machine learning group at LIS Lab, he co-organized the inaugural Quantum Machine Learning workshop at ECML-PKDD 2022 and serves as Vice-president of SSFAM (Société Savante Francophone d’Apprentissage Machine), actively shaping the European ML research landscape.

Mathieu BrédifView profile

Researcher

• Lidar Processing
• 3D Reconstruction
• Geovisualization
• +5 more

Mathieu Brédif is a Permanent Researcher at LASTIG, Gustave Eiffel University, affiliated with the National School of Geographic Sciences (ENSG) and IGN. He serves as co-chair of ISPRS Working Group II/3 on Point Cloud Processing (2016-2020) and chaired ISPRS Working Group III/5 on Graphics and Remote Sensing (2012-2016). His academic appointments include Assistant Professor at École Polytechnique teaching Image Analysis and Computer Vision (INF573) and 3D Computer Graphics (INF443) since 2019-2020. Telecom ParisTech PhD (2005-2010) Stanford University Master in Computer Science (2004) École Polytechnique Engineering Degree (2000-2005) Brédif's research focuses on Lidar processing, 3D reconstruction, and geovisualization , with significant contributions to point cloud analysis, urban scene modeling, and historical image integration. His work bridges computer vision, photogrammetry, and geographic information systems, emphasizing practical applications in urban planning and cultural heritage. He has developed novel algorithms for point cloud inpainting, visibility estimation, and distributed 3D reconstruction. His publications reveal consistent focus on urban modeling through point cloud processing (58% of works), image-based rendering techniques (22%), and geovisualization systems (15%). The research trajectory shows increasing emphasis on deep learning applications for LiDAR data since 2016, alongside continued development of geometric algorithms for photogrammetric processing. ANR project leadership in geospatial data valorization (structurAtion et vaLorisation du patrimoinE géoGraphique - 9) iSpace&Time 4D web GIS development (5) European project participation in high-volume point cloud analysis (8) Brédif actively mentors doctoral candidates, currently supervising Melvin Hersent, Alexane Nghien, and Florent Geniet, with 8 completed PhDs including Pierre Biasutti and Murat Yirci. His laboratory work centers on the GEOVIS research team , developing the iTowns open-source framework for 3D geospatial visualization, which powers the Géoportail's 3D data engine and supports multiple ANR projects in cultural heritage visualization.

Raji Susan MathewView profile

Assistant Professor

• Medical Imaging
• Image Reconstruction
• Compressed Sensing
• +3 more

Raji Susan Mathew is an Assistant Professor at the School of Data Science, Indian Institute of Science Education and Research Thiruvananthapuram (IISER TVM). Her research focuses on regularization techniques, compressed sensing, and deep learning for medical image reconstruction, particularly in magnetic resonance imaging (MRI) and quantitative susceptibility mapping (QSM). Current affiliation: School of Data Science, IISER TVM Prior appointments: C. V. Raman Postdoctoral Fellow and Research Associate III at Indian Institute of Science, Bangalore Education: Ph.D. in MR image reconstruction from IIIT-Kerala, M.Tech in Signal Processing from Cochin University of Science and Technology, B.Tech in Electronics and Communication Engineering from Mahatma Gandhi University Her recent publications highlight expertise in AI-driven medical imaging solutions, including QSM optimization , vision transformers for nerve tracking , and unsupervised learning for corrosion analysis . She has also contributed to book chapters on parallel MRI theory and regularization frameworks. Scientific awards include the C. V. Raman Postdoctoral Fellowship and Maulana Azad National Fellowship , supporting her work on efficient algorithms for medical image processing. Dr. Mathew advises Ph.D. and BS-MS students on topics like spiking neural networks in imaging , uncertainty-aware QSM reconstruction , and lightweight AI models for disease classification . She actively reviews for journals like IEEE Transactions on Medical Imaging and conferences like ISBI and ICASSP.

Christophe KervazoView profile

Assistant Professor

• Sparse Blind Source Separation
• Nonnegative Matrix Factorization
• Hyperspectral Imaging
• +4 more

Christophe Kervazo is an Assistant Professor (Maître de Conférences) at Télécom Paris, France, affiliated with the IMAGES group under the Image, Data, Signal (IDS) department . His research focuses on sparse blind source separation, nonnegative matrix factorization, hyperspectral imaging, and optimization techniques for remote sensing and biomedical applications. Education: Engineering degree from Supélec (2015), Master of Science from Georgia Institute of Technology (2016), PhD in Signal and Image Processing from Université Paris Saclay (2019). His work spans deep learning for inverse problems (including deep unrolling techniques), remote sensing (hyperspectral imaging and SAR), and uncertainty quantification . Recent publications address synthetic data training for medical imaging, distributed sparse BSS, and nonlinear component separation. Collaborators include institutions like CEA Saclay, Université de Mons, and ONERA. Current students include PhD candidates working on topics such as digital breast tomosynthesis, hyperspectral unmixing, and SAR image reconstruction. Former students and interns have contributed to projects involving plug-and-play methods, unrolling algorithms, and implicit regularization. He is involved in teaching and research projects, including collaborations with Airbus and ONERA on hyperspectral imaging and spectral band optimization. His lab, LTCI (Information Processing and Communication Laboratory), supports interdisciplinary work in signal and image processing.

David CohenView profile

Professor

• Child and Adolescent Psychiatry
• Autism Spectrum Disorders
• Neurodevelopmental Disorders
• +7 more

David Cohen is a University Professor and Hospital Practitioner affiliated with the ACIDE team at AP-HP (Assistance Publique - Hôpitaux de Paris). His research spans child and adolescent psychiatry , autism spectrum disorders , and neurodevelopmental conditions , with a focus on integrating social robotics and affective computing into clinical interventions. His recent work explores AI-based analysis of child-therapist interactions , ICT applications for neurodevelopmental disorders , and robot-assisted therapies . Key publications include systematic reviews on depression assessment tools in autism, longitudinal studies of emotional interventions, and collaborative research on human-robot interaction in clinical contexts. David Cohen collaborates extensively with teams across clinical psychology , robotics , and public health , contributing to journals like Journal of Autism and Developmental Disorders , Research in Developmental Disabilities , and Frontiers in Psychiatry . No specific awards, grants, or educational credentials are detailed in the provided texts.

Guillaume CaronView profile

Associate Professor

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

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

Zhiyang ShenView profile

Associate Professor

• Environmental and Energy Economics
• Efficiency and Productivity Analysis
• Banking Performance Evaluation
• +4 more

Zhiyang Shen is an Associate Professor at the IÉSEG School of Management, specializing in Economics with a focus on Environmental and Energy Economics, Efficiency Analysis, and Sustainable Development. He holds a Ph.D. in Economics from the University of Lille 1 (2016) and an HDR (Habilitation) in Economics from the University of Lille (2023). His research explores the intersection of digital technology, energy transitions, and environmental policy, with a particular emphasis on green productivity and climate resilience in developing economies. Education: 2023: HDR in Economics, University of Lille, France 2016: Ph.D. in Economics, University of Lille 1, France 2013: Master in Public Economics and Public Finance, University of Rennes, France 2012: Master of Business Administration, Rouen Business School, France Research Interests: Shen’s work centers on measuring and improving environmental and economic efficiency through advanced methodologies like Data Envelopment Analysis (DEA). He investigates topics such as energy transitions, carbon neutrality strategies, and the role of digital technologies in fostering sustainable growth. His studies often address policy-relevant questions in China and other Belt and Road countries. Publications: His recent work highlights themes such as green productivity decomposition, energy security, and the impact of digitalization on energy efficiency. Key contributions include analyzing agricultural productivity in Belt and Road nations and evaluating renewable energy policies in China. Professional Experience: 2022–present: Associate Professor, IÉSEG School of Management 2020–2022: Assistant Professor, Beijing Institute of Technology 2013–2022: Research and Teaching roles at IÉSEG 2017–2020: Economic Analyst/Manager, China Ex-Im Bank 2009–2011: Civil Servant, Bengbu Municipal Bureau of Finance Labs/Teams: Member of the Laboratory of Economics and Management (LEM) at IÉSEG.