Keynote Speakers
Keynote Speaker I
Prof. Tae-Kyun Kim, Korea Advanced Institute of Science and Technology, Korea
Tae-Kyun (T-K) Kim is a full Professor and the director of Computer Vision and Learning Lab at School of Computing, KAIST since 2020, and has been an adjunct reader of Imperial College London (ICL), UK for 2020-2024. He led Computer Vision and Learning Lab at ICL during 2010-2020. He obtained his PhD from Univ. of Cambridge in 2008 and Junior Research Fellowship (governing body) of Sidney Sussex College, Univ. of Cambridge during 2007-2010. His BSc and MSc are from KAIST. His research interests primarily lie in machine (deep) learning for 3D computer vision and generative AI, including: articulated 3D hand/body reconstruction, face analysis and recognition, 6D object pose estimation, activity recognition, object detection/tracking, active robot vision, which lead to novel active and interactive visual sensing. He has co-authored over 100 academic papers in top-tier conferences and journals in the field, and has co-organised series of HANDS workshops and 6D Object Pose workshops (in conjunction with CVPR/ICCV/ECCV) since 2015. He was the general chair of BMVC17 in London, the program co-chair of BMVC23, and is Associate Editor of Pattern Recognition Journal, Image and Vision Computing Journal. He regularly serves as an Area Chair for top-tier vision/ML conferences. He received KUKA best service robotics paper award at ICRA 2014, and 2016 best paper award by the ASCE Journal of Computing in Civil Engineering, and the best paper finalist at CVPR 2020, and his co-authored algorithm for face image representation is an international standard of MPEG-7 ISO/IEC.
Keynote Speaker II
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Prof. Changxu Wu
Tsinghua University, China
Dr. Changxu Wu received his Ph.D.
degree in Industrial and Operational Engineering from
the University of Michigan-Ann Arbor (2007). He is a
full professor of Department of Industrial Engineering
in Tsinghua University, China since 2020. From
2017-2020, he was a professor of Department of Systems
and Industrial Engineering University of Arizona. Dr. Wu
directs the Cognitive System Lab and he is interested in
integrating cognitive science and engineering system
design, especially modeling human cognition system with
its applications in system design, improving
transportation safety, promoting human performance in
human-computer interaction, and inventing innovative
sustainable and smart energy systems with human in the
loop. Dr. Wu has published 116 papers in the field
including 80 journal papers, 36 conference papers, 1
book chapter, and 2 patents in intelligent system design
authorized. The journal papers include IEEE Transactions
on Systems, Man, and Cybernetics (Part A), IEEE
Transactions on Intelligent Transportations Systems,
Psychological Review (Impact Factor: 9.02), ACM
Transactions on Computer-Human Interaction,
International Journal of Human-Computer Studies, as well
as several other journals. He was the Chair of Human
Performance Modeling Technical Group of Human Factors
and Ergonomics Society (HFES) in USA. He is also
Associate Editors for IEEE Transactions on Intelligent
Transportations Systems, IEEE Transaction on
Human-Machine Systems, and Behaviour & Information
Technology. He received the Senior Researcher of the
Year Award from the Dean of School the Engineering &
Applied Sciences at SUNY Buffalo and Outstanding Student
Instructor Award from the American Society of
Engineering Education (ASEE).
Invited Speaker
Invited Speaker I
Prof. Maxim Bakaev, Novosibirsk State Technical University, Russia
Maxim Bakaev
got his PhD degree in Software Engineering in 2012.
He currently works as Associate Professor of the
Automated Control Systems department of Novosibirsk
State Technical University (NSTU), Russia. He is
also the Acting Head of the Data Collection and
Processing Systems department. Previously, he
received his Master Degree in Digital Design from
Kyungsung University, South Korea. His research
interests include Human-Computer Interaction,
Universal Design, Web User Interfaces, User Behavior
Models, Knowledge Engineering, Machine Learning,
etc.
(https://www.researchgate.net/profile/Maxim-Bakaev)
His recent research results are related to
perception of visual complexity in graphical user
interfaces (UIs) and its relation to Gestalt
principles and compression algorithms. So, he has
proposed the Index of Difficulty for tasks that
involve visual-spatial working memory. He oversees
the development of the Web UI Measurement Platform
(http://va.wuikb.info/) that integrates online
services for collecting ML data for UI assessment.
He has served as a committee member for several
international conferences, particularly as PC
Co-Chair for ICMSC 2018 and ICWE 2019, as Demo &
Posters Chair for ICWE 2020, and as Workshops
Co-Chair for ICWE 2021. He also served as a reviewer
for several international conferences and journals,
including CHI, UIST, International Journal of
Human-Computer Studies, Applied Ontology, Symmetry,
etc. He is the Guest Editor for "Complexity in
Human-Computer Interfaces: Information-Theoretic
Approaches and Beyond", a Special Issue in
Mathematics journal. He is also a Section Editor for
the Journal of Web Engineering. He has acted as PI
or participant in several research grants, domestic
and international. In 2016, he received Novosibirsk
City Hall award in science and innovations as a
"Best young researcher in higher education
institutions". Under his supervision, more than 20
Master and Bachelor students graduated.