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James Tin-Yau KWOK ( |
| Biography |
Prof Kwok received his B.Sc. degree in Electrical and Electronic Engineering from the University of Hong Kong and his Ph.D. degree in computer science from the Hong Kong University of Science and Technology. He then joined the Department of Computer Science, Hong Kong Baptist University as an Assistant Professor. He returned to the Hong Kong University of Science and Technology and is now a Professor in the Department of Computer Science and Engineering. He is serving / served as an Associate Editor for the IEEE Transactions on Neural Networks and Learning Systems, Neural Networks, Neurocomputing, Artificial Intelligence Journal, International Journal of Data Science and Analytics, and on the Editorial Board of Machine Learning. He is also serving as Senior Area Chairs of major machine learning / AI conferences including NeurIPS, ICML, ICLR, IJCAI, and as Area Chairs of conferences including AAAI and ECML. He is on the IJCAI Board of Trustees. He is recognized as the Most Influential Scholar Award Honorable Mention for "outstanding and vibrant contributions to the field of AAAI/IJCAI between 2009 and 2019". Prof Kwok is the IJCAI-2025 Program Chair.
| Research |
Machine learning,
Deep learning,
Data mining,
Artificial intelligence
Applications:
Computer vision and image processing,
speech processing,
pervasive computing
List of publications
(Google
scholar)
Best Teaching Award, MSc Program in Big
Data Technology, 2021-2022
Best Paper Runner-Up, Applied Research Track, International Conference on Information and Knowledge Management (CIKM), 2022
Best Review Award, International Conference on Learning Representations (ICLR), 2017
Nomination for the Best Paper Award, SIAM International Conference on Data Mining (SDM), 2010.
Second Class Award in Natural Sciences by the Ministry of Education, People's Republic of China, 2008
IEEE Transactions on Neural Networks Outstanding
Paper Award,
2004
Quanming Yao,
First Runner-up, Ph.D. Research Excellence (HKUST Engineering School), 2018-2019
Quanming Yao,
Google PhD Fellowship in Machine Learning, 2016.
Wei Bi,
Google Anita Borg Fellowship, 2014.
Wei Bi,
Google PhD Fellowship in Machine Learning, 2013.
Ivor Tsang,
Best Paper Award, IEEE Hong Kong Chapter of Signal Processing
Postgraduate Forum, 2006.
Ivor Tsang,
Microsoft Fellowship, 2005.
Weiyu
Chen (PhD student)
Yunhao Gou (PhD student)
Ruping Huang (PhD student)
Zhili Liu (PhD student)
Yanbin Wei (PhD student)
Hansi Yang (PhD student)
Xilin Cao (MPhil student)
Kai Syun Hou (MPhil student)
Weiqing Xu (MPhil student)
Lifeng
Shen (PhD 2024)
Weisen Jiang (PhD 2024)
Han
Shi (PhD 2022)
Shuai Zheng (PhD 2019)
Lu
Hou (PhD 2019)
Yaqing Wang (PhD 2019; co-supervised with
Lionel Ni)
Quanming Yao (PhD 2018)
Wei
Bi (PhD 2015)
Leon Wenliang Zhong (PhD 2014)
Kai Zhang (PhD 2008)
Ivor Tsang (PhD 2007, MPhil
2003)
Nai Chit Fung (MPhil 2024)
Jincheng Yu (MPhil 2024)
Runsheng Yu (MPhil 2024)
Lawrence Chan (MPhil 2021)
Minsam Kim (MPhil 2020)
Zachary William Wellmer (MPhil 2019)
Xiawei Guo (MPhil 2017)
Yihai Huang (MPhil 2015)
Pak-Ming Cheung (MPhil
2006)
Calvin Chu (MPhil 2005)
| Teaching |
MSBD5008: Introduction to Social Computing
MSBD5012: Machine Learning
MFIT5004: Financial Data Mining
SBMT5710: Artificial Intelligence (for MBA)
COMP171: Data Structures and Algorithms
COMP271: Design and Analysis of Algorithms
COMP327: Introduction to Pattern Recognition
COMP344: Image Processing
COMP3211: Introduction to Artificial Intelligence
COMP4211: Machine Learning (UG)
COMP4331: Introduction to Data Mining
COMP4641: Social Information Networks Analysis and Engineering
COMP5212: Machine Learning (PG)
COMP621I: Advanced Topics in Machine Learning
COMP621O: Kernel Methods in Machine Learning
| Other Links |
Matrix
Reference
Manual,
MathWorld,
Wikipedia,
Alpha,
Google,
Lbsearch
HKUST:
IEEE Explore,
SCI,
JSTOR,
E-journals,
Library,
Intranet for staff ,
CSD Webmail,
Outlook,
FYP,
Canvas
More WWW sites
)