| Prof. Liming ChenÉcole Centrale de Lyon Liming Chen is a Distinguished Professor of Artificial Intelligence at École Centrale de Lyon and a senior member of the Institut Universitaire de France (IUF). He received his BSc in Mathematics and Computer Science from the University of Nantes in 1984, and his MSc and PhD in Computer Science from the University Pierre and Marie Curie (Paris 6) in 1986 and 1989, respectively. Prof. Chen began his academic career as an Associate Professor at the Université de Technologie de Compiègne, before joining École Centrale de Lyon as a full professor in 1998. He has also held industrial positions, notably as Chief Scientific Officer of Avivias and as multimedia expert for France Telecom R&D China. From 2007 to 2016, he served as Head of the Department of Mathematics and Computer Science at École Centrale de Lyon. His research focuses on computer vision, machine learning, and robotics. Over the past decade, his group is at the forefront of DA research and has brought major advances to both shallow and deep DA, from geometry-aware robust alignment to global prior-aware learning for visual recognition and conditional diffusion-based cross-domain generation. These methods consistently achieved state-of-the-art results on standard DA benchmarks, validating their robustness and scalability. Prof. Chen has authored over 300 peer-reviewed publications, supervised more than 40 PhD students, and led numerous EU and national research projects. He has guest-edited six high profile journal special issues and serves as Area Editor for Computer Vision and Image Understanding. He is a Senior Member of the IEEE. |
| Prof. Jie YangShanghai Jiao Tong University Jie Yang received a bachelor’s degree in Automatic Control in Shanghai Jiao Tong University (SJTU), where a master’s degree in Pattern Recognition & Intelligent System was achieved three years later. In 1994, he received Ph.D. at Department of Computer Science, University of Hamburg, Germany. Now he is the Professor and Director of Institute of Image Processing and Pattern recognition in Shanghai Jiao Tong University. He is the principal investigator of more than 30 national and ministry scientific research projects in image processing, pattern recognition, data mining, and artificial intelligence. He has published six books，more than five hundreds of articles in national or international academic journals and conferences. Google citation over 27500，H-index 85. Up to now, he has supervised 5 postdoctoral, 46 doctors and 70 masters, awarded six research achievement prizes from ministry of Education, China and Shanghai municipality. He has owned 48 patents. Three Ph.D. dissertation he supervised was evaluated as “National Best Ph.D. Dissertation” in 2009, in 2017, in 2019. He has been chairman and keynote speaker of more than 10 international conferences. He is in the list of 2025 World Top 2% Career-long Impact Scientists issued by Stanford University and Elsevier. |
| Prof.Rémi EmonetJean Monnet UniversityRémi Emonet is a Professor at Jean Monnet University, in Saint-Étienne and head of the Machine Learning team of the Hubert Curien Laboratory and member of the Inria-MALICE team. He holds an engineering degree from ENSIMAG and a Ph.D. in software architectures for intelligent environments that he defended in 2009 at INRIA Grenoble. He did a 3-year postdoctoral stay at Idiap Research Institute in Switzerland, before being recruited as a lecturer at Jean Monnet University in Saint-Étienne in 2013. He has worked on a variety of topics including computer vision, probabilistic generative models, anomaly detection and transfer learning. Rémi Emonet is an Junior IUF laureate, with a project on exploring the extensions of optimal transport to structured data. The main challenges concern problem formulations, the design of scalable algorithms, and the study of their theoretical guarantees. He also investigates the connections between optimal transport and generative models such as diffusion models and flow matching. |
| Research Director. Carole LartizienCNRS, CREATIS Laboratory Carole Lartizien is a CNRS Research Director at CREATIS laboratory in Villeurbanne, France. She received the Bachelor’s degree in nuclear engineering from the National Polytechnic Institute, Grenoble, France and a Master’s degree in Biomedical Engineering from Lyon University in 1997. In 2001, she obtained a PhD in medical image processing from Paris XIII University for her work at the CEA in Orsay, France in collaboration with Siemens Healthineers, on machine learning analysis of positron emission tomography (PET) images for cancer research. After completing a post-doctorate at the University of Pittsburgh in the United States, Carole Lartizien joined the CREATIS laboratory in Villeurbanne in 2004 as a researcher at the CNRS. She has been a research director at the CNRS Institute of Computer Science since 2018. Carole Lartizien has recognized expertise in statistical modelling and analysis of cancer and neuro-imaging. She has developed strong background over the past years on deep unsupervised representation learning and anomaly detection for brain pathologies. She has been involved as a principal investigator or co-investigator of several national and European projects and has a strong experience in student supervision (> 16 PhDs and 30 master students). She is involved in the organization of scientific events (MIDL 24) and sits on the scientific committees of several conferences. She co-authors more than 120 papers in international journals and conferences in the field. |
