Find Academic Supervisors

Adriana Tapus is a Full Professor at ENSTA Paris, affiliated with Institut Polytechnique de Paris, leading the Autonomous Systems and Robotics Laboratory (SAR) within the Computer Science and Systems Engineering Unit (U2IS). She holds an HDR (Habilitation) and a PhD from EPFL, Switzerland, with postdoctoral experience at USC. Her research focuses on socially assistive robotics, human-robot interaction (HRI), and personalized therapy for individuals with physical/cognitive impairments. She directs the IP Paris Doctoral School and coordinates national/international projects like the EU-funded ENRICHME and SWEET. Education: PhD in Mobile Robotics, EPFL (2005) Habilitation (HDR), ENSTA Paris (2011) M.S. Computer Science, University Joseph Fourier Engineer, Politehnica University of Bucharest Research Interests: Tapus pioneers socially assistive robotics, integrating machine learning, human modeling, and multimodal communication (verbal/non-verbal/para-verbal). Her work addresses adaptive therapies for vulnerable populations using robotics, physiological data interpretation, and context-aware interaction. Key themes include: Human-robot cooperation and trust Emotion recognition and expression Personalized rehabilitation systems AI ethics and human-centered design Publications: Over 150 articles, with recent work exploring humor in HRI, teleoperation trust models, and cross-cultural intelligent vehicles. Notable 2025 contributions include studies on robot laughter efficacy and multimodal facial expression frameworks. Awards: 2025: 4 IROS papers accepted 2016: 25 Women in Robotics recognition 2010: Romanian Academy Award Multiple conference best paper awards (RO-MAN, ICRA, etc.) Advising & Grants: Supervised over 20 PhD students and led projects like EU Horizon 2020 ENRICHME. Current students focus on teleoperation dynamics, robot humor, and haptic interfaces. Active in editorial roles (IJSR, THRI) and conference organization (HRI General Chair 2019). Labs/Teams: Founder of RoboticsByDesign lab and co-initiator of the Hi! Paris interdisciplinary AI center. The SAR lab develops systems for healthcare, education, and human-robot collaboration.

• Robotics
• Human-Robot Interaction
• Machine Learning
• +7 more

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.

• Industry 5.0
• Logistics and Supply Chain Optimization
• Digital Twin
• +4 more

Kévin Bailly is a Lecturer at Sorbonne University, affiliated with the Institute of Intelligent Systems and Robotics (ISIR) and part of the Machine Learning and Artificial Intelligence (MLIA) team. His research focuses on computer vision, deep learning, and their applications in facial expression recognition, neural network optimization, and medical imaging. Dr. Bailly's research interests span multiple areas including: Computer Vision and Image Analysis Deep Learning and Neural Network Optimization Facial Expression and Action Unit Recognition Model Compression and Quantization Techniques Medical Applications of Artificial Intelligence His recent publications demonstrate a strong focus on neural network optimization, with particular emphasis on quantization, pruning, and compression techniques that maintain model performance while reducing computational requirements. His work spans both theoretical advancements in deep learning and practical applications in healthcare, human-computer interaction, and affective computing. He has developed novel approaches like PowerQuant for non-uniform quantization, RULe for real-time face alignment in degraded conditions, and RED++ for data-free pruning of deep neural networks. Dr. Bailly has published extensively in top-tier venues including ICLR, NeurIPS, IEEE TPAMI, and IEEE TAC, with a consistent output of high-impact research from 2022-2024. His work bridges theoretical computer vision with practical applications, particularly in medical diagnostics and human-computer interaction systems. He actively collaborates with researchers across multiple institutions, including Arnaud Dapogny, Edouard Yvinec, and Matthieu Cord, and has contributed to interdisciplinary projects that apply AI techniques to medical domains such as fracture classification and obstetrics.

• Computer Vision
• Facial Expression Recognition
• Deep Learning
• +4 more

Mondher Feki is an Associate Professor of Management at Université Paris-Saclay, focusing on IS/IT management and digital transformation. His research explores blockchain applications in supply chains, robotic process automation (RPA), robo-advisors, and generative AI. He teaches Management Information Systems and Data Management courses. Currently serving as a reviewer for journals like Business & Information Systems Engineering and conferences like HICSS and ECIS. Active member of the Association Information & Management (AIM). Key research areas include digital transformation strategies, blockchain's operational impact, AI-driven financial advisory systems, and RPA implementation in insurance sectors. His work emphasizes technology adoption challenges and strategic alignment in business contexts. Recent publications analyze blockchain use in French retail logistics, RPA benefits for Allianz France, and IS quality's strategic role in firm performance. Conference contributions address robo-advisors in crowdfunding and pandemic-driven higher education innovation. Maintains active academic service roles in peer review and conference organization.

• Business Value of IT/IS
• Digital Transformation
• Robotic Process Automation
• +3 more

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.

• Robotics
• Computer Vision
• Machine Learning
• +4 more

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.

• Human-Machine Interaction (HMI)
• Augmented Reality (AR)
• Virtual Reality (VR)
• +4 more

Daniela Maresch is an Associate Professor at GEM, affiliated with the Management, Technologies and Strategy Department since December 2020. She holds a PhD in Business Administration and an LL.M. in Business Law from WU Vienna University of Business and Economics (Austria), followed by a postdoctoral qualification (Habilitation) from Johannes Kepler University Linz (Austria). Her research focuses on entrepreneurship, regional development, and innovation, particularly in areas like entrepreneurial finance, technology entrepreneurship, social/migrant entrepreneurship, and education. Her work bridges interdisciplinary fields, combining legal, economic, and managerial perspectives. Dr. Maresch’s research has been published in journals such as Journal of Corporate Finance , Technological Forecasting and Social Change , and the European Central Bank Working Paper Series, with funding from the EU, the Swedish Kamprad Family Foundation, and private enterprises. She has held visiting roles at Aalto University (Finland), Cranfield University (UK), Lund University (Sweden), and currently serves as a visiting professor at Johannes Kepler University Linz. She is also an editorial board member for Technological Forecasting and Social Change and Review of Managerial Science . Her research explores themes such as entrepreneurial ecosystems, scaling strategies in digital eras, and the socio-economic impact of disruptive technologies. Key themes include innovation adoption in SMEs, governance of emerging technologies (e.g., additive manufacturing), and the role of fear-of-missing-out in decision-making. She advocates for policies fostering scalable ventures and ethical considerations in technology deployment, such as moral frameworks for social robots. Dr. Maresch’s work addresses challenges in rural entrepreneurship, including social enterprise sustainability and innovation. She collaborates with academic and industry partners to advance practical applications of her research, emphasizing interdisciplinarity and real-world relevance.

• Entrepreneurship
• Regional Development
• Innovation
• +5 more

Alex 'Sandy' Pentland is a Professor of Media Arts and Sciences at the MIT Media Lab, where he helped create and direct both the MIT Media Lab and Media Lab Asia in India. He also serves as a HAI Fellow at Stanford University. Pentland is one of the most-cited computational scientists globally and was named by Forbes as one of the '7 most powerful data scientists in the world.' Pentland's educational background includes undergraduate studies at the University of Michigan and a Ph.D. in artificial intelligence and psychology from MIT. His research spans computational social science, organizational engineering, wearable computing (including Google Glass), image understanding, and modern biometrics. His recent publications reveal a strong focus on the intersection of AI and social systems, with emphasis on human-AI coevolution, data ethics, network science, and the societal implications of digital technologies. His work increasingly addresses critical issues in data privacy, tokenized asset networks, and the social contract in the age of big data, demonstrating his continued leadership in shaping how society understands and manages digital transformation. MIT's Toshiba endowed chair Election to the U.S. Academy of Engineering McKinsey Award from Harvard Business Review 40th Anniversary of the Internet from DARPA Brandeis Award for work in privacy Pentland has advised over 80 PhD students, with nearly half now tenured faculty at leading institutions, a quarter leading industry research groups, and the remainder founding their own companies. His research has attracted significant funding, evidenced by projects like the DARPA Network Challenge where his team won by applying data-driven approaches to crowd coordination. His work on 'reality mining' has led to practical applications in call centers, mental health services, and urban planning. As director of the Human Dynamics group at MIT, Pentland has pioneered sociometric sensors and reality mining techniques. His lab has incubated numerous companies including Ginger.io (mental health services), CogitoCorp.com (AI coaching), Wise Systems (delivery optimization), Sila Money (financial technology), and several others focused on data privacy and AI applications across various sectors.

• Computational Social Science
• Wearable Computing
• Reality Mining
• +6 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.

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

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

Ahed Alboody is a Professor and Researcher at HESAM University Group, specifically affiliated with CESI and the Digital Innovation Laboratory for Businesses and Learning to Support Territorial Competitiveness (LINEACT) in Nice, France. He holds a specialized doctorate in computer science from the University of Toulouse 3 Paul Sabatier and has extensive experience in deep learning, computer vision, and remote sensing applications. His work bridges academic research with practical applications in environmental monitoring, human-computer interaction, and spatial reasoning systems. Education: Specialized Doctorate in Computer Science, University of Toulouse 3 Paul Sabatier (IRIT), 2011 Master 2 Research in Electronics, Automation and Systems Engineering, National Polytechnic Institute of Toulouse (INPT-ENSEEIHT), National School of Civil Aviation (ENAC), ISAE-SUPAERO, and University of Toulouse III, 2006 Engineering Diploma in Electronics and Telecommunications, University of Tishreen (Techrine), Lattakia, Syria, 2002-2003 Undergraduate studies in Electronics and Telecommunications, University of Tishreen (Techrine), Lattakia, Syria, 2002 Alboody's research focuses on advanced applications of deep learning and computer vision, particularly in the areas of 3D hand gesture recognition, hyperspectral and multispectral image processing, and semantic segmentation. His work combines theoretical advancements in mixture-of-experts architectures with practical applications in remote sensing and environmental monitoring. He has pioneered approaches in frugal learning and zero-shot learning for image segmentation tasks, with applications in digital twins and collaborative robot environments. His publication record demonstrates a clear evolution from foundational work in spatial reasoning systems (2008-2012) to current cutting-edge research in deep learning architectures for 3D gesture recognition and hyperspectral image analysis. Recent publications (2022-2024) show a strong focus on mixture-of-experts transformers, parallel architectures for efficient computation, and applications in environmental monitoring with drones and satellite imagery. Alboody actively supervises Master's level research projects (two M2 level projects mentioned) and serves as a reviewer for prestigious journals including IEEE Transactions on Neural Networks and Learning Systems and IEEE Transactions on Geoscience and Remote Sensing. He has also been a member of the Technical Program Committee for international conferences on databases and knowledge applications. His laboratory work centers around the Digital Innovation Laboratory for Businesses and Learning to Support Territorial Competitiveness (LINEACT), where he leads research in engineering and digital tools. Current projects include developing graph neural networks for 3D hand gesture recognition using depth and skeleton data, and implementing frugal learning approaches for semantic image segmentation in collaborative robot environments.

• Deep Learning
• Machine Learning
• Computer Vision
• +9 more

Professor Mahdi Mahfouf holds a Chair in the School of Electrical and Electronic Engineering at the University of Sheffield. He has held academic roles since 1997, progressing from Lecturer to Professor in 2005. His research focuses on Fuzzy Logic, Control Systems, and their applications in biomedical and industrial contexts. Mahfouf leads the Intelligent Systems Research Laboratory and has contributed over 370 publications, including influential work on fuzzy modeling and predictive control. Education: Ing.Dipl. (Hons) in Control Systems MPhil in Control Systems (University of Sheffield, 1988) PhD in Control Systems (University of Sheffield, 1991) Research Interests: Fuzzy Logic applications, Artificial Intelligence, Neural Networks, Model-Based Predictive Control, Biomedical Engineering (e.g., ICU Decision Support Systems), and Manufacturing Systems (e.g., granulation processes, surface metrology). Key Achievements: Recipient of the IEE Hartree Premium Award (1992) and MEDIPEX Innovation Award. His work integrates fuzzy logic into real-time systems for aviation, healthcare, and robotics. Grants & Labs: Leads the Intelligent Systems Research Lab. Active in collaborative projects with industry (e.g., pharmaceuticals, aerospace). His research bridges theory and practice, emphasizing data-driven solutions for complex systems.

• Fuzzy Logic
• Artificial Intelligence
• Neural Networks
• +6 more

Liming Chen is a Full Professor and Director of the Department Mathématiques - Informatique at École Centrale de Lyon, Université de Lyon. As a member of the Laboratoire d'Informatique en Image et Systèmes d'Information (LIRIS, UMR 5205), his research spans computer vision, pattern recognition, and multimedia computing. His extensive research portfolio includes 3D face analysis, image/video categorization, affect analysis, and biometric systems. He has led significant projects such as ANR 3D Face Analyzer, ANR Videosense, ANR Omnia, and ANR FAR3D, focusing on advanced recognition systems and multimodal analysis. Professor Chen supervises multiple PhD students and has developed open-source tools for 3D model processing. His work has received recognition through best performance awards at international competitions including SHREC 2011 (3D face recognition) and ImageCLEF 2011 (photo annotation).

• Computer Vision
• Pattern Recognition
• 3D Face Analysis
• +2 more

Pierre Renaud is a Professor at INSA Strasbourg and Deputy Director of the ICube laboratory, specializing in Medical and Surgical Robotics, Mechatronics, and Additive Manufacturing. His research focuses on developing advanced robotic systems for healthcare applications, including surgical robots, compliant mechanisms, and MRI-compatible devices. He leads projects such as SPIRIT (multi-material additive manufacturing for medical robotics) and contributes to national initiatives like TIRREX and LABEX CAMI. Education: PhD in Mechanics from Université Clermont-Auvergne (2003), M.Sc. from ENS Cachan (1998), and Agrégation in Mechanical Engineering (1999). Visiting Associate Professor at Stanford University (2010–2011) as a Fulbright Fellow. Research Themes: Mechatronics for medical robotics, compliant systems, additive manufacturing integration, and tensegrity-based robots. Collaborates with IHU Strasbourg for surgical technology development and Axilum Robotics for industrial applications. Key Projects: Robotic assistance for interventional radiology, magnetic elastography, and beating heart surgery. Active in international collaborations (e.g., ANR, H2020 ITN ATLAS). Labs/Teams: Head of the Robotics, Data Science, and Healthcare Technologies group at ICube. Engaged in Equipex IRIS and ROBOTEX platforms for robotic innovation.

• Medical and Surgical Robotics
• Robotics
• Mechatronics
• +5 more

Grégory Batt is a Researcher and Head of the InBio joint research group at the Institut Pasteur and Inria Paris. The lab operates at the intersection of wet and dry biology, focusing on systems and synthetic biology with an emphasis on automation, modeling, and real-time control of cellular processes. The team is affiliated with both institutions and hosts a multidisciplinary group of researchers, engineers, and students. The research interests of Grégory Batt span systems biology, synthetic biology, quantitative modeling, lab automation, bioproduction, and single-cell analysis . His work integrates computational and experimental approaches to develop frameworks for understanding and controlling cellular behavior. Key methodologies include the use of synthetic biology, microfluidics, optogenetics, and robotics. The lab has developed innovative software tools such as ReacSight and MicroMator to enable automated and reactive experimentation. Recent publications highlight trends in real-time control of bioproduction, optimization of protein secretion, parameter inference in stochastic models, and ecological frameworks for antibiotic resistance . These works demonstrate a strong focus on integrating modeling with high-throughput experimentation to solve problems in biotechnology and medicine. Scientific contributions include: Development of ReacSight for bioreactor automation and reactive control Creation of MicroMator for reactive microscopy Application of ecological concepts to bacterial antibiotic responses Modeling stochastic kinetics coupled with auxiliary processes Batt advises several PhD students and postdoctoral researchers, including Henri Galez, Alicia Da Silva, Cecilia Capela, and Viktoriia Gross. His lab has received support from ANR, Inria, and other funding bodies. The InBio team operates a state-of-the-art laboratory equipped with bioreactors, liquid handling robots, flow cytometers, automated microscopes, and high-performance computing resources, enabling advanced research at both population and single-cell levels. The lab, located at the Yersin and Lwoff buildings of the Institut Pasteur in Paris, fosters a collaborative environment integrating molecular biology, microbiology, and computational modeling to advance quantitative understanding of cellular systems.

• Systems biology
• Synthetic biology
• Quantitative modeling
• +15 more