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.