Keynote Speakers

Prof. Hiroyuki Kudo
University of Tsukuba, Japan

Prof. Hiroyuki Kudo received the B.Sc. degree from the Department of Electrical Communications, Tohoku University, Japan, in1985, and the Ph.D. degree from the Graduate School of Engineering, Tohoku University, in 1990. In 1992, he joined the University of Tsukuba, Japan. He is currently a Professor with the Institute of Systems and Information Engineering, University of Tsukuba, Japan. His research areas include medical imaging, image processing, and inverse problems. In particular, he is actively working on tomographic image reconstruction for X-ray CT, PET, SPECT, and electron tomography. He received best paper awards more than 10 times from various international and Japanese societies. He received the IEICE (The Institute of Electronics, Information, and Communication Engineers, Japan) Fellow award for his contributions on “cross-sectional image reconstruction methods in medical computed tomography”. In 2018, he obtained Commendation for Science and Technology by the Minister of Education, Culture, Sports, Science and Technology for his contributions on “research on design method and image reconstruction method for new CT”. For 2011-2016, he was an Editor-in-Chief of the Journal of Medical Imaging Technology (MIT). From 2020, he is a president of Japanese Society of Medical Imaging Technology (JAMIT).



Prof. Ce Zhu
IEEE Fellow

University of Electronic Science and Technology of China, China

Ce Zhu has been with University of Electronic Science and Technology of China (UESTC), Chengdu, China, as a Professor since 2012, and serves as the Dean of Glasgow College, a joint school between the University of Glasgow, UK and UESTC, China. His research interests include video coding and communications, video analysis and processing, 3D video, visual perception and applications. He has served on the editorial boards of a dozen journals, including as an Associate Editor of IEEE TRANSACTIONS ON IMAGE PROCESSING, IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, IEEE TRANSACTIONS ON BROADCASTING, IEEE SIGNAL PROCESSING LETTERS, an Editor of IEEE COMMUNICATIONS SURVEYS AND TUTORIALS, and an Area Editor of SIGNAL PROCESSING: IMAGE COMMUNICATION. He has also served as a Guest Editor of multiple special issues in international journals, including as a Guest Editor in the IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING.
Prof. Zhu is an IEEE/Optica/IET/AAIA Fellow. He serves as the Chair of IEEE ICME Steering Committee (2024-2025). He was an IEEE Distinguished Lecturer of Circuits and Systems Society (2019-2020), and also an APSIPA Distinguished Lecturer (2021-2022). He is a co-recipient of multiple paper awards at international conferences, including the most recent Best Demo Award in IEEE MMSP 2022, and the Best Paper Runner Up Award in IEEE ICME 2020.



Prof. Amir Hussain

Edinburgh Napier University, UK

Amir Hussain obtained his B.Eng (1st Class Honours with distinction) and Ph.D from the University of Strathclyde in Glasgow, UK, in 1992 and 1997 respectively. Following an UK EPSRC funded Postdoctoral Fellowship (1996-98) and Research Lectureship at the University of Dundee, UK (2018-20), he joined the University of Stirling, UK, in 2000 where he was appointed to a Personal Chair in Cognitive Computing in 2012. Since 2018, he has been Director of the Centre of AI and Robotics at Edinburgh Napier University, UK. His research and innovation interests are cross-disciplinary and industry-led, aimed at developing trustworthy AI and cognitive data science technologies to engineer the smart healthcare and industrial systems of tomorrow. He has co-authored over 600 papers including around 300 journal papers (h-index: 73, 22,000+ citations) and 20 Books, and supervised over 40 PhD students. He has led major national and international projects, including as Principal Investigator of the current multi-million pound COG-MHEAR programme (funded under the UK EPSRC Transformative Healthcare Technologies for 2050 Call) that aims to develop truly personalised assistive hearing and communication technologies. He is the founding Chief Editor of (Springer's) Cognitive Computation journal and Editorial Board member for (Elsevier’s) Information Fusion and various IEEE Transactions. Amongst other distinguished roles, he is Executive Committee member of the UK Computing Research Committee (the national expert panel of the IET and BCS for UK computing research). He served as General Chair of the 2020 IEEE WCCI (the world’s largest IEEE technical event on computational intelligence, comprising the flagship IJCNN, IEEE CEC and FUZZ-IEEE) and the 2023 IEEE Smart World Congress (featuring six co-located IEEE Conferences).

Speech Title: Trustworthy Artificial Intelligence: Real-world Use Cases, Challenges and Opportunities

Abstract: TBA  



Prof. Yen-Wei Chen
Ritsumeikan University, Japan

Yen-Wei Chen received the B.E. degree in 1985 from Kobe Univ., Kobe, Japan, the M.E. degree in 1987, and the D.E. degree in 1990, both from Osaka Univ., Osaka, Japan. He was a research fellow with the Institute for Laser Technology, Osaka, from 1991 to 1994. From Oct. 1994 to Mar. 2004, he was an associate Professor and a professor with the Department of Electrical and Electronic Engineering, Univ. of the Ryukyus, Okinawa, Japan. He is currently a professor with the college of Information Science and Engineering, Ritsumeikan University, Japan. He is the founder and the first director of Center of Advanced ICT for Medicine and Healthcare, Ritsumeikan University.
His research interests include medical image analysis, computer vision and computational intelligence. He has published more than 300 research papers in a number of leading journals and leading conferences including IEEE Trans. Image Processing, IEEE Trans. Medical Imaging, CVPR, ICCV, MICCAI. He has received many distinguished awards including ICPR2012 Best Scientific Paper Award, 2014 JAMIT Best Paper Award. He is/was a leader of numerous national and industrial research projects. Professor Yen-Wei Chen is ranked in the World’s top 2% of scientists for both the single recent year (2023) and career-long (updated until to end-of-2022), according to Stanford/Elsevier's rankings.