Dr. Ruidan Su received his Ph.D. in Computer Application Technology from Northeastern University, in 2014. From 2015 to 2020, he served as an Assistant Professor at the Shanghai Advanced Research Institute, Chinese Academy of Sciences. He is currently with the Artificial General Intelligence (AGI) Institute, School of Computer Science, Shanghai Jiao Tong University (SJTU). Dr. Su has published over 37 peer-reviewed papers in journals and conference proceedings. His research interests include artificial intelligence, AI for materials science, and AI applications in medical imaging and finance. He is an IEEE Senior Member and has served as Program Chair of the MICAD conference series since its inaugural edition in 2020.Prof. Yudong Zhang is the Honorary Follow of World Leadership Academy, Fellow of IET, Fellow of EAI, and Fellow of BCS. He is the Senior Member of IEEE, IES, and ACM. He is the Distinguished Speaker of ACM. He was included in Most Cited Chinese Researchers (Computer Science) by Elsevier from 2014 to 2018. He was 2019-2025 recipient of Clarivate Highly Cited Researcher. He is included in World’s Top 2% Scientist by Stanford University from 2020 to 2025. His three papers are included in UK Research Excellence Framework (REF) 2021. His citation reached 46k in Google Scholar (h-index 115). Prof. Alejandro F. Frangi FREng is the Bicentenary Turing Chair in Computational Medicine at The University of Manchester (UK), with joint appointments in the Schools of Computer Science and Health Sciences. His research spans medical image analysis, computational imaging, and precision computational medicine, including image-based modelling, AI, and in silico trials for medical devices. He has authored 320+ journal articles and held major leadership roles in the medical imaging community, including editorial and conference leadership at MICCAI and IEEE.

• Enhancing Transfer Learning Techniques for Improved Medical Imaging.- A Comprehensive Evaluation of Bidirectional MRI-CT Generation Methods Considering Three Factors: Dataset, Model, and Training Strategy.- Symmetry-Aware Brain MRI Inpainting Using Denoising Diffusion Models.- InfoMotion: A Graph-Based Approach to Video Dataset Distillation for Echocardiography.

Dr. Ruidan Su received his Ph.D. in Computer Application Technology from Northeastern University, in 2014. From 2015 to 2020, he served as an Assistant Professor at the Shanghai Advanced Research Institute, Chinese Academy of Sciences. He is currently with the Artificial General Intelligence (AGI) Institute, School of Computer Science, Shanghai Jiao Tong University (SJTU). Dr. Su has published over 37 peer-reviewed papers in journals and conference proceedings. His research interests include artificial intelligence, AI for materials science, and AI applications in medical imaging and finance. He is an IEEE Senior Member and has served as Program Chair of the MICAD conference series since its inaugural edition in 2020.Prof. Yudong Zhang is the Honorary Follow of World Leadership Academy, Fellow of IET, Fellow of EAI, and Fellow of BCS. He is the Senior Member of IEEE, IES, and ACM. He is the Distinguished Speaker of ACM. He was included in Most Cited Chinese Researchers (Computer Science) by Elsevier from 2014 to 2018. He was 2019-2025 recipient of Clarivate Highly Cited Researcher. He is included in World’s Top 2% Scientist by Stanford University from 2020 to 2025. His three papers are included in UK Research Excellence Framework (REF) 2021. His citation reached 46k in Google Scholar (h-index 115). Prof. Alejandro F. Frangi FREng is the Bicentenary Turing Chair in Computational Medicine at The University of Manchester (UK), with joint appointments in the Schools of Computer Science and Health Sciences. His research spans medical image analysis, computational imaging, and precision computational medicine, including image-based modelling, AI, and in silico trials for medical devices. He has authored 320+ journal articles and held major leadership roles in the medical imaging community, including editorial and conference leadership at MICCAI and IEEE.

• Enhancing Transfer Learning Techniques for Improved Medical Imaging.- A Comprehensive Evaluation of Bidirectional MRI-CT Generation Methods Considering Three Factors: Dataset, Model, and Training Strategy.- Symmetry-Aware Brain MRI Inpainting Using Denoising Diffusion Models.- InfoMotion: A Graph-Based Approach to Video Dataset Distillation for Echocardiography.

Dr. Ruidan Su received his Ph.D. in Computer Application Technology from Northeastern University, in 2014. From 2015 to 2020, he served as an Assistant Professor at the Shanghai Advanced Research Institute, Chinese Academy of Sciences. He is currently with the Artificial General Intelligence (AGI) Institute, School of Computer Science, Shanghai Jiao Tong University (SJTU). Dr. Su has published over 37 peer-reviewed papers in journals and conference proceedings. His research interests include artificial intelligence, AI for materials science, and AI applications in medical imaging and finance. He is an IEEE Senior Member and has served as Program Chair of the MICAD conference series since its inaugural edition in 2020.Prof. Yudong Zhang is the Honorary Follow of World Leadership Academy, Fellow of IET, Fellow of EAI, and Fellow of BCS. He is the Senior Member of IEEE, IES, and ACM. He is the Distinguished Speaker of ACM. He was included in Most Cited Chinese Researchers (Computer Science) by Elsevier from 2014 to 2018. He was 2019-2025 recipient of Clarivate Highly Cited Researcher. He is included in World’s Top 2% Scientist by Stanford University from 2020 to 2025. His three papers are included in UK Research Excellence Framework (REF) 2021. His citation reached 46k in Google Scholar (h-index 115). Prof. Alejandro F. Frangi FREng is the Bicentenary Turing Chair in Computational Medicine at The University of Manchester (UK), with joint appointments in the Schools of Computer Science and Health Sciences. His research spans medical image analysis, computational imaging, and precision computational medicine, including image-based modelling, AI, and in silico trials for medical devices. He has authored 320+ journal articles and held major leadership roles in the medical imaging community, including editorial and conference leadership at MICCAI and IEEE.

• Enhancing Transfer Learning Techniques for Improved Medical Imaging.- A Comprehensive Evaluation of Bidirectional MRI-CT Generation Methods Considering Three Factors: Dataset, Model, and Training Strategy.- Symmetry-Aware Brain MRI Inpainting Using Denoising Diffusion Models.- InfoMotion: A Graph-Based Approach to Video Dataset Distillation for Echocardiography.