|Degree||Ph.D. in Eng.|
|Affiliation||Information and Management Systems Engineering, Graduate Shool of Engineering 情報・経営システム工学専攻|
|Lessons in charge||Basics of Statistics, Human Interface Engineering, Artificial Intelligence, Machine Learning, Intelligent Informatics|
|Research Focus||Intelligent Informatics, Computational Intelligence, Affective Informatics, Human Computer Interactions|
|Key Topic||■Theories and Applications on Automated Reasoning, Machine Learning and Knowledge Discovery under Uncertainty: Fuzzy Logic, Possibility theory, Dempster-Shafer theory of Evidence, Rough Sets, Bayesian Reasoning, etc. ■ Affective Design Technologies Requiring Affective Images and Originality ■ Descriptive Decision-Making under Uncertainty ■ Intelligent Human Interfaces|
|Belonging Societies||IEEE, SOFT, JSKE, IEICE, JSAI, HIS|
|Laboratory||Intelligent Informatics and Human Computer Interactions|
We are studying theories, techniques and applications of Computational Intelligence, a sub-field of Artificial Intelligence. The difference of CI from the conventional AI based on Mathematical Logic and Symbolism is that CI tries to solve the real world problems with a variety of metaheuristics which are a set of general-purpose intelligent heuristics or procedures. In the lab we study theories and techniques to deal with uncertainty inevitable in the real world (Fuzzy logic, Rough sets, Evidence theory, Probability, etc.), evolutionary computation that mimics creatures’ evolution, and machine learning that utilizes the past experience as well as their applications such as affective engineering that supports humans to design products with required affective images, human-computer interactions that let humans collaborate with computers, and social computing that supports human social behaviors.