Junzo Watada

Waseda University, Japan

In data analysis, machine learning plays a pivotal role in obtaining the latent structure of data. When employing meta-heuristic methods in machine learning, these methods enable us to provide efficient and effective results for the machine leaning. The talk explains such models used in various analyses from imbalanced dataset problem to bilevel quadratic programming problem.

Biography

He received the B.Sc. and M.Sc. degrees in electrical engineering from Osaka City University, Japan, and the Ph.D degree from Osaka Prefecture University, Japan. Currently he is a professor of Management Engineering, Knowledge Engineering and Soft Computing at the Graduate School of Information, Production & Systems, Waseda University, Japan. He is a recipient of Henri Coanda Medal Award from Inventico in Romania in 2002. He is a Life Fellow of Japan Society for Fuzzy Theory and intelligent informatics (SOFT). Dr. Watada is the Executive Chair of World Collaborative Innovative Center as well as the Executive Chair of International Society of Management Engineers. Also he concerns with various international journals, including Journal of Systems and Control Engineering (I MECH E), Fuzzy Optimization & Decision Making, IEEE trans on SMCB, Information Sciences, KES IDT journal, IJICIC, and ICIC Express Letters, His professional interests include soft computing, tracking system, knowledge engineering and global management engineering.