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'; Prof. Shun-Feng Su

Professor

Shun-Feng Su received the B.S. degree in electrical engineering from National Taiwan University, Taiwan, R.O.C., in 1983, and the M.S. and Ph.D. degrees in electrical engineering from Purdue University, West Lafayette, Indiana, in 1989 and 1991, respectively.

He is a Chair Professor of the Department of Electrical Engineering, National Taiwan University of Science and Technology, Taiwan, R.O.C. He also is the Vice President for research in that university since 2023. He is a Fellow for various societies, including IEEE, IFSA, CACS, TFSA, and RST. He has published more than 300 refereed journal and conference papers in the areas of robotics, intelligent control, fuzzy systems, neural networks, and non-derivative optimization. His current research interests include intelligent control, computational intelligence, machine learning, intelligent manufacturing, data science, and robotics.

Dr. Su is very active in various international/domestic professional societies. He now is the Vice President for publication of the IEEE SMC society. He also serves as a board member of various academic societies. Dr. Su also acted as General Chair, Program Chair, or various positions for many international and domestic conferences. Dr. Su currently serves as associate editors of IEEE Transactions on Cybernetics, of IEEE Transactions on Fuzzy Systems, and of Information Science, a senior editor and associate editor of IEEE Access, the executive editor of the Journal of the Chinese Institute of Engineers, and an area editor and associate editor of International Journal of Fuzzy Systems.
Email: sfsu@mail.ntust.edu.tw; TEL: 886-2-2733-3141#6704

Current Position

  • IEEE Fellow;
  • CACS Fellow;
  • Member of board of Government, IEEE Systems, Man, and Cybernetics society;
  • Member of Supervisory Committee, Taiwan Fuzzy System Association;

Research Area

  • Numerical Learning Theorems (Learning Algorithms、Network Structure Design、Robust Learning Analysis、Parallel learning Design);
  • Optimization Techniques (Ant Systems、Swarm Algorithm、Networks Evolution Approaches);
  • Intelligent Control Theorems and Applications (Neural Control、Fuzzy Control Analysis and Design、Online Learning Control);
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