Keynote Speakers
(Alphabetize by Last Name)
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Prof. Tae-Kyun Kim |
Tae-Kyun (T-K) Kim is 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 Imperial College 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 in 1998 and 2000, he worked at Samsung AIT for 2000-2004 (military duty). His research interests primarily lie in machine (deep) learning for 3D computer vision, generative AI and Physics-based 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 to 2020. He was the general chair of BMVC17 in London, the program co-chair of BMVC23, and is Associate Editor of IEEE Trans on PAMI, 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.
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Prof. Yong Zhang |
Prof. Yong Zhang is currently a Chair Professor of Biomedical Engineering and Head of Department of Biomedical Engineering at City University of Hong Kong (CityUHK). Before he joined CityUHK, he had over 20 years of working experience in Department of Biomedical Engineering at National University of Singapore (NUS). He joined NUS as an Assistant Professor in 2002 and was promoted to Associate Professor in 2007, to Professor in 2013, and to Provost’s Chair Professor in 2017. He developed new technology for point-of-care diagnostics, photodynamic therapy, and optogenetics based on smart nanomaterials and wearable/implantable devices. His publications in top-tier journals (Nature Medicine, Nature Biomedical Engineering, Nature Communications, PNAS, Advanced Materials, etc.), many plenary/keynote/invited talks in international conferences, his contribution to academic communities and professional societies, and his effort in technology translation/commercialization, made him an internationally recognized researcher. His research achievements have been featured in magazines and news media, such as Nature, The Straits Times, and Lianhe Zaobao. He has received many awards, such as Global STEM Professorship (Hong Kong), Humboldt Research Award (Germany), and IES Prestigious Engineering Achievement Award (Singapore). He is a Fellow of Singapore Academy of Engineering (FSAEng), International Academy of Medical and Biological Engineering (IAMBE), American Institute for Medical and Biological Engineering (AIMBE), European Academy of Sciences and Arts, Institute of Electrical and Electronics Engineers (IEEE), and Royal Society of Chemistry (FRSC). He is also named as a Highly Cited Researcher by Clarivate Analytics and listed on World’s Top 2% Scientists by Stanford University and Elsevier BV.
Invited Speakers
(Alphabetize by Last Name)
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Prof. Keqin Liu |
Prof. Keqin Liu received his PhD degree from the University of California at Davis in 2010 and joined industry as a software engineer in 2012 after 2 years of postdoc experience. After 8 years of working in the Silicon Valley, Prof. Liu still has a lot passion in mathematics and decided to return to academia in 2020 when working in ASML and subsequently taught in Nanjing University until joining Xi’an Jiaotong-Liverpool University in 2024. Prof. Liu’s research interests include the development of modern math theory for AI technologies, the extension of pure math theory, especially number theory, and the application of pure math theory to solving practical problems in machine learning, e.g., multi-armed bandit in reinforcement learning. Prof. Liu has published over 40 academic papers in top international journals and conferences including Management Science, IEEE Transactions on Information Theory, and NeurIPS. Prof. Liu has received the 2023 Zhi-Jian Award for Excellence in Teaching (mathematics) from Nanjing University, the 2024 SIP International Leading Talent Award from Suzhou, and the 2025 Excellent Research-led Learning Supervisor Award from Xi’an Jiaotong-Liverpool University.
Title: High-Dimensional Reinforcement Learning by Multi-Armed Bandits
Abstract: The main challenge in machine learning is the complexity of high-dimensional problems. The way of data sampling itself becomes crucial during the learning evolution process. The tradeoff between exploration and exploitation is well modeled by the Multi-armed Bandit (MAB) problems. In this talk, we present some recent results from my own group on the techniques innovated to solve such high-dimensional reinforcement learning problems. Furthermore, we will illustrate the process of transforming pure math theories into applied fields for efficient algorithm developments and optimizations.
To be announced soon...
Part of Previous Speakers
(Alphabetize by Last Name)
Prof. Pingyi Fan
Tsinghua University, China
Assoc. Prof. Paul Weng
Duke Kunshan University, China
Prof. Bingang Xu
The Hong Kong Polytechnic University, Hong Kong, China
Prof. Zhijie Xu
Xi’an Jiaotong-Liverpool University, China