Academic Qualification
Ph.D. in Computing, The Hong Kong Polytechnic University
Bachelor in Computer Studies, The City University of Hong Kong
Teaching Areas
LP002: Data Structures in C
ME001: Information Systems Analysis and Design
MIIZ04: Advanced Topics in Information Technology
LP003: Object Oriented Programming
CN104: Computer Programming and Design II
CN003: Computer Programming I
MA003, MATH100: Linear Algebra
MA006: Discrete Mathematics
CS105: Fundamentals of Artificial Intelligence
CS360, SE360: Artificial Intelligence
Research Interests
Rough Sets
Fuzzy Rough Sets
Granular Computing
Concept-cognitive Learning
Deep Learning
Fuzzy Logic, Sets and Systems
Genetic Algorithm
Professional Services
IEEE Transactions on Systems, Man, and Cybernetics, Part B. 6/2004—12/2014.
International Journal of Machine Learning and Cybernetics, since 1/2017
Advances in Computational Intelligences, since 10/2020
Working Experiences
Assistant Professor, Dept. of Computing, Hong Kong Polytechnic University
Assistant Professor, Macau University of Science and Technology
Associate Professor, Macau University of Science and Technology
Professor, Macau University of Science and Technology
Reviewers of Journal Papers
IEEE Transactions on Neural Networks
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Systems, Man and Cybernetics
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Knowledge and Data Engineering
International Journal of Pattern Recognition and Artificial Intelligence
Fuzzy Sets and Systems
Information Sciences
Knowledge - based Systems, etc.
Academic Publication (selected)
1. M Hu, Eric C. C. Tsang, Y. T. Guo, W. H. Xu, “Fast and robust attribute reduction based on the separability in fuzzy decision systems”, IEEE Transactions on Cybernetics, 2022, 52(6), 5559 - 5572.
2. M Hu, Eric C. C. Tsang, Y. T. Guo, Q. S. Zhang, D. G. Chen, W. H. Xu, “A novel approach to concept-cognitive learning in interval-valued formal contexts: a granular computing viewpoint”. International Journal of Machine Learning and Cybernetics, 2022,13(4), 1049-1064.
3. Chengling Zhang, Eric C.C. Tsang, Weihua Xu, Yidong Lin and Lanzhen Yang, “Incremental concept-cognitive learning approach for concept classification oriented to weighted fuzzy concepts”, Knowledge-Based Systems, Volume 260, 25 January 2023, 110093.
4. M Hu, Y Guo, D Chen, Eric C. C. Tsang, Q Zhang, “Attribute reduction based on neighborhood constrained fuzzy rough sets”, Knowledge-Based Systems, Volume 274, 15 August 2023, 110632.
5. Qingshuo Zhang E.C.C. Tsang Qiang He Yanting Guo, “Ensemble of kernel extreme learning machine based elimination optimization for multi-label classification”, Knowledge-Based Systems, Volume 278, 25 October 2023, 110817.
6. Zhang Q, Tsang E C C, He Q, et al. “Distance metric learning with local multiple kernel embedding”, International Journal of Machine Learning and Cybernetics, 2023, 14(1): 79-92.
7. Jiaming Wu, Eric C.C. Tsang, Weihua Xu, “Correlation concept-cognitive learning model for multi-label classification”, accepted for publication, Knowledge Based Systems, 2024.
8. Chengling Zhang, Eric C.C. Tsang, Weihua Xu, Yidong Lin, Lanzhen Yang, Jiaming Wu, “Dynamic updating variable precision three-way concept method based on two-way concept-cognitive learning in fuzzy formal contexts”, Information Sciences, Volume 655, January 2024, 119818.
9. Lanzhen Yang, Eric C.C. Tsang, Xizhao Wang, Chengling Zhang, “ELM parameter estimation in view of maximum likelihood”, Neurocomputing Volume 557, 7 November 2023, 126704.