Prof. CHEUNG, Yiu Ming
Prof. CHEUNG, Yiu Ming

張曉明教授
BSc, MPhil, PhD, FIEEE, FAAAS, FIET, FBCS, FAAIA, RGC Senior Research Fellow
Chair Professor, Department of Computer Science
https://www.comp.hkbu.edu.hk/~ymc/
 

About

Prof. Cheung received the PhD degree from the Department of Computer Science and Engineering at the Chinese University of Hong Kong. Currently, he is a Chair Professor (Artificial Intelligence) of Department of Computer Science, and Dean of Institute for Research and Continuing Education (IRACE) in Hong Kong Baptist University (HKBU). Prof. Cheung is a Fellow of IEEE, AAAS, IET, BCS, and AAIA. He is the awardee of RGC Senior Research Fellow with receiving a fellowship grant of HK$7.8 million over a period of 60 months. Also, he is the recipient of 2023 APNNS Outstanding Achievement Award. He was elected as a Distinguished Lecturer of IEEE Computational Intelligence Society in 2020, and the Changjiang Scholar (Chair Professor) awarded by Ministry of Education of China. He is currently the Editor-in-Chief of IEEE Transactions on Emerging Topics in Computatitional Intelligence. Also, he is serving as an Associate Editor for IEEE Transactions on Cybernetics, Pattern Recognition, Pattern Recognition Letters, and Neurocomputing, just to name a few.


Research Interests

  • Machine Learning
  • Visual Computing
  • Data Science
  • Pattern Recognition
  • Multi-objective Optimization
  • Information Security

Selected Publications

 
  1. H.M. Cai, Y. Hu, F. Qi, B. Hu and Y.M. Cheung*, “Deep Tensor Spectral Clustering Network via Ensemble of Multiple Affinity Tensors”, IEEE Transactions on Pattern Analysis and Machine Intelligence, in press, DOI: 10.1109/TPAMI.2024.3361912.
  2. H.M. Cai, W.T. Huang, S.R. Yang, S.Q. Ding, Y. Zhang, B. Hu, F. Zhang and Y.M. Cheung*, “Realize Generative yet Complete Latent Representation for Incomplete Multi-view Learning”,  IEEE Transactions on Pattern Analysis and Machine Intelligence, in press, DOI: 10.1109/TPAMI.2023.3346869.
  3. W.C. Lan, Y.M. Cheung*, J.Y. Jiang, Z.K. Hu and M.K. Li, “Compact Neural Network via Stacking Hybrid Units”, IEEE Transactions on Pattern Analysis and Machine Intelligence, in press, DOI: 10.1109/TPAMI.2023.3323496.
  4. M.K. Li, Y.M. Cheung* and Z.K. Hu, “Key Point Sensitive Loss for Long-tailed Visual Recognition”, IEEE Transactions on Pattern Analysis and Machine Intelligence, 45(4): 4812-4825, 2023.
  5. Y.Q. Zhang and Y.M. Cheung*, “Learnable Weighting of Intra-attribute Distances for Categorical Data Clustering with Nominal and Ordinal Attributes”, IEEE Transactions on Pattern Analysis and Machine Intelligence, 44(7): 3560-3576, 2022.
  6. X. Liu, K. Hu, H.B. Ling and Y.M. Cheung*, “MTFH: A Matrix Tri-Factorization Hashing Framework for Efficient Cross-Modal Retrieval”, IEEE Transactions on Pattern Analysis and Machine Intelligence, 43(3): 964-981, 2021.
  7. Y. Zhou and Y.M. Cheung*, “Bayesian Low-Tubal-Rank Robust Tensor Factorization with Multi-Rank Determination”, IEEE Transactions on Pattern Analysis and Machine Intelligence, 43(1): 62-76, 2021.
  8. Y.M. Cheung* and Y.Q. Zhang, “Fast and Accurate Hierarchical Clustering Based on Growing Multi-Layer Topology Training”, IEEE Transactions on Neural Networks and Learning Systems, 30(3): 876-890, 2019.
  9. H. Zeng and Y.M. Cheung*, “Feature Selection and Kernel Learning for Local Learning Based Clustering”, IEEE Transactions on Pattern Analysis and Machine Intelligence, 33(8): 1532-1547, 2011.
  10. Y.M. Cheung*, “Maximum Weighted Likelihood via Rival Penalized EM for Density Mixture Clustering with Automatic Model Selection”, IEEE Transactions on Knowledge and Data Engineering, 17(6): 750-761, 2005.

(Note: * Corresponding Author)