Plenary Speakers

Introduction & Speech Abstracts

Prof. Maode Ma

Dr. Maode Ma received his Bachelor degree from Department of Computer Science and Technology in Tsinghua University in 1982, his Master degree from Department of Computer Science and Technology in Tianjin University in 1991, and his Ph.D. degree in Department of Computer Science from Hong Kong University of Science and Technology in 1999. Now, Dr. Ma is an Associate Professor in the School of Electrical and Electronic Engineering at Nanyang Technological University in Singapore. He has extensive research interests including network security and wireless networking. He has led and/or participated in 20 research projects funded by government, industry, military and universities in various countries. He has been a general chair, technical symposium chair, tutorial chair, publication chair, publicity chair and session chair for more than 80 international conferences. He has been a member of the technical program committees for more than 180 international conferences. Dr. Ma has about 300 international academic publications including over 130 journal papers and more than 160 conference papers. He has edited 4 technical books and produced over 20 book chapters. He has delivered over 40 keynote speeches and more than 10 tutorials at various international conferences. He currently serves as the Editor-in-Chief of International Journal of Computer and Communication Engineering and International Journal of Electronic Transport. He also serves as a Senior Editor for IEEE Communications Surveys and Tutorials, and an Associate Editor for International Journal of Network and Computer Applications, International Journal of Security and Communication Networks, International Journal of Wireless Communications and Mobile Computing and International Journal of Communication Systems. He had been an Associate Editor for IEEE Communications Letters from 2003 to 2011. Dr. Ma is the Fellow of IET and a senior member of IEEE Communication Society and IEEE Education Society. He is the Chair of the IEEE Education Society, Singapore Chapter. He is serving as an IEEE Communication Society Distinguished Lecturer from 2013 to 2016.

Prof. Wei-Chang Yeh

Dr. Wei-Chang Yeh has published more than 140 papers in reputed journals, 50 patents, and 60 conference papers. He is an International Fellow of Chinese Innovation and Invention Society, the EIC of “The Open Cybernetics & Systemic Journal” and “Soft Computing with Applications”; an AE of IEEE Transactions on Reliability, an editorial board member of Reliability Engineering and System Safety (RESS), Journal of Applied Mathematics, and International Journal of Management and Marketing. Dr. Wei-Chang Yeh is most honored to be able to serve as IEEE Computational Intelligence Society Intelligent Systems Applications Technical Committee, and the Task Force Chair for the IEEE Intelligent Adaptive Fault Tolerant Control, Optimization and Reliability.(

"Simplified Swarm Optimization and its Applications"


The optimization problem which is the problem we are going to deal with in this talk.

  1. SSO(Simplified Swarm Optimization): SSO is short for Simplified Swarm Optimization and it is the major tool to solve the optimization problem.
  2. Various Update Mechanism of SSO: The Update Mechanism is the fingerprint of soft computing. Each soft computing method has its own and unique update mechanism. The development history of SSO is only less than 7 years, but there are more than 10 different various update mechanism based on the fundamental update mechanism of the SSO.
  3. Hybrid with others(to show the flexibility of SSO): The way to hybrid with other Soft Computing Methods, such as PSO, GA, SA, ABC, and so on.
  4. Discussion the Parameter setting of SSO: Soft computing always needs to set up many parameters in applications. Hence, the parameter setting is always a big issue among all Soft computing. A good parameter setting will result in a great outcome.

    The optimization problem is a problem to find the best solution from all feasible solutions. The optimization problem is very important in the real world. Researchers have studied numerous optimization problems during these decades from various perspectives. For example, the supply chain management, the grid computing, reliable systems design, data mining, etc. A lots of methods have been proposed to find the exact solutions of optimization problems. For example, the Kamarka method for linear programming, Dijkstra algorithm for the Shortest Path Problem, branch-and-bound for these NP-hard or NP-complete problems, and so on. However, these optimization problems that can be solved in polynomial time are very fewer since most of the extension of the optimization problems in the real-life applications are NP-complete or NP-hard. For example, even only few change to the original optimization problems can make these optimization problems became NP-hard, e.g., integer variables, nonlinear equations, and/or multi-objectives. Moreover, analytical methods such as branch-and-bound, which try to obtain optimal solutions, cannot solve NP-complete or NP-hard problems with a few hundred integer variables in an acceptable amount of time. There is always a need to solve an optimization problem even we can not have its exact solution. Hence, the main focus has been on developing approximation methods to reduce the computation burden.

Prof. Hong Yan

Hong Yan received his Ph.D. degree from Yale University. He was professor of imaging science at the University of Sydney and currently is chair professor of computer engineering at City University of Hong Kong. He was elected an IAPR fellow for contributions to document image analysis and an IEEE fellow for contributions to image recognition techniques and applications. Professor Yan was a Distinguished Lecturer of IEEE SMC Society during 2000 to 2015. He received the 2016 Norbert Wiener Award from IEEE SMC Society for contributions to image and biomolecular pattern recognition techniques.(

Professor Yan's research interests include:
Bioinformatics: Genomic data analysis; Structural biology
Image processing: Biomedical imaging; Document imaging
Pattern recognition: Clustering and biclustering; Human face recognition and animation