1. Academic Summary
Masashi Sugiyama is a leading Japanese researcher in machine learning and statistical data analysis, known for both theoretical foundations and practical machine learning methods. He currently directs RIKEN AIP while holding a professorship at The University of Tokyo where he develops modern AI methods.
2. Education
Bachelor of Engineering (B.Eng.) — Tokyo Institute of Technology, Japan (1997).
Master of Engineering (M.Eng.) — Tokyo Institute of Technology, Japan (1999).
Doctor of Engineering (Dr.Eng.) — Tokyo Institute of Technology, Japan (2001).
3. Professional Experience
Director, RIKEN Center for Advanced Intelligence Project (AIP) (since 2016).
Professor, Department of Complexity Science and Engineering, Graduate School of Frontier Sciences, The University of Tokyo (since 2014).
Previously Assistant & Associate Professor, Tokyo Institute of Technology.
4. Research Interests
Masashi Sugiyama’s research includes:
Statistical Machine Learning
Weakly Supervised Learning & Reinforcement Learning
Theory and Algorithms of Data Analysis
Density Ratio Estimation & Statistical Inference
Machine Learning in Non-Stationary Environments
He has authored influential textbooks on these topics.
5. Selected Publications & Books
He co-authored key machine learning monographs:
Machine Learning in Non-Stationary Environments (MIT Press).
Density Ratio Estimation in Machine Learning (Cambridge University Press).
Statistical Reinforcement Learning (CRC Press).
Introduction to Statistical Machine Learning (Morgan Kaufmann).
Machine Learning from Weak Supervision (MIT Press).
6. Honors & Awards
Japan Academy Medal (2017) — one of the top honors in Japanese science.
Commendation for Science and Technology, Minister of Education, Culture, Sports, Science and Technology (2022).