Masashi Sugiyama
Masashi Sugiyama (Ph.D.)
Team Leader
2001Assistant Professor, Department of Computer Science, Graduate School of Information Science and Engineering, Tokyo Institute of Technology, Tokyo, Japan.
2003Associate Professor, Department of Computer Science, Graduate School of Information Science and Engineering, Tokyo Institute of Technology, Tokyo, Japan.
2014Professor, Department of Complexity Science and Engineering, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan. (Present)
2016Director, RIKEN Center for Advanced Intelligence Project, Tokyo, Japan. (Present)


  • Team leader
    Masashi Sugiyama
  • Research scientist
    Gang Niu
  • Postdoctoral researcher
    Jingfeng Zhang
  • Postdoctoral researcher
    Jiaqi Lyu
  • Postdoctoral researcher
    Shuo Chen
  • Senior visiting scientist
    Shinichi Nakajima
  • Visiting scientist
    Futoshi Futami
  • Visiting scientist
    Florian Yger
  • Visiting scientist
    Takashi Ishida
  • Visiting scientist
    Miao Xu
  • Visiting scientist
    Takayuki Osa
  • Visiting scientist
    Bo Han
  • Visiting scientist
    Yuko Kuroki
  • Visiting scientist
    Takahiro Mimori
  • Visiting scientist
    Feng Liu
  • Visiting scientist
    Lei Feng
  • Visiting scientist
    Tongliang Liu
  • Part-time worker I
    Masahiro Fujisawa
  • Part-time worker I
    Yifan Zhang


Recently, machine learning technology with big data has been actively investigated and its effectiveness has been demonstrated. However, depending on application domains, it is difficult or even it is not possible to collect a large amount of data. In the Imperfect Information Learning Team, for various machine learning tasks including supervised learning, unsupervised learning, and reinforcement learning, we develop novel algorithms that allow accurate learning from limited information. We also elucidate their theoretical properties and apply them to various real-world applications ranging from fundamental science to business.

Main Research Field
Computer Science
Research Field
Engineering / Mathematics
Research Subjects
Development of machine learning algorithms from imperfect information
Theoretical analysis of machine learning algorithms
Real-world application of machine learning algorithms


Related posts

posted on November 17, 2022 16:39Seminar
posted on November 15, 2022 10:08Information
posted on November 11, 2022 13:18Seminar
posted on October 27, 2022 10:49Seminar
posted on October 25, 2022 14:52Seminar
posted on October 26, 2022 14:13Seminar
posted on October 26, 2022 14:57Seminar
posted on October 13, 2022 18:41Seminar
posted on October 3, 2022 09:05Seminar
posted on September 27, 2022 19:29Information
posted on September 3, 2022 09:27Seminar
posted on August 17, 2022 11:57Seminar
posted on August 2, 2022 13:41Seminar
posted on June 10, 2022 18:44Seminar
posted on April 28, 2022 11:56Seminar
posted on April 4, 2022 16:13InformationAward
posted on April 8, 2022 14:02InformationAward
posted on March 9, 2022 15:20Seminar
posted on March 9, 2022 15:22Seminar
posted on February 3, 2022 15:41Seminar
posted on February 8, 2022 11:35Seminar
posted on February 8, 2022 11:41Seminar
posted on January 30, 2022 21:18Seminar
posted on January 26, 2022 19:35Information
posted on January 25, 2022 14:15Seminar
posted on October 8, 2021 16:33Information
posted on March 9, 2021 16:01Information
posted on January 29, 2021 13:48Information
posted on January 26, 2021 15:17Information
posted on January 27, 2021 11:12Information
posted on October 2, 2020 09:00Information
posted on December 5, 2019 09:30Information
posted on September 11, 2019 12:00Information
posted on August 8, 2019 10:45Information
posted on September 7, 2018 17:55Information