Hiroshi Mamitsuka got all degrees (B.S., M.E. and PhD) from University of Tokyo, Japan. After working with industry in business data mining for more than 10 years, he joined academia for doing research on machine learning and scientific data mining. Currently he is a professor of Institute for Chemical Research, Kyoto University, Japan, being jointly appointed as a faculty of School of Pharmaceutical Sciences of the same university. Also he is currently a visiting professor of Department of Computer Science, Aalto University, Finland. His research interests are machine learning, data mining and a wide variety of applications.

 

SESSIONS

KEYNOTE 2 
Machine Learning Techniques and Applications: Past, Present and Future

Wednesday, November 27  | 9.00am – 9.45am
Auditorium 2

Machine learning is data-driven and thus application-driven technology. In this sense machine learning techniques have been developed to meet the demand of applications. I will first review current and past machine learning techniques, introducing a typical example of such tight relationships between the application requirement and learning technology development. I will then look ahead the future to shed light on possible, promising future applications, which are already gradually coming out.