Takeshi Teshima, Ph.D.

Hi! I’m Takeshi Teshima. I’m a Data Scientist at Recruit Co., Ltd.

Previously, I received Ph.D. in Science from the University of Tokyo in 2022 (advisor: Professor Masashi Sugiyama, Graduate School of Frontier Sciences), M.Sc. in Science in 2019 (same as PhD), and B.Econ. in 2017 (Department of Economics). I’m an alumni of the Sugiyama-Yokoya-Ishida Laboratory, and I was a Junior Research Associate at RIKEN AIP (national research center). I am currently supported by Masason Foundation.

In previous years, I have been honored to closely work with Professor Issei Sato as well as many other exceptional collaborators. My next career goal is to contribute to “AI for Good” with innovative ideas.

Research Interests 🔗

I’ve always been interested in generic methodology. I am currently working on developing statistical machine learning as one of the major frontiers of statistics/information technology. For more details, please visit the research introduction page.

  • Causality for learning from small data.
    • Transfer learning based on similarity of causal mechanisms (causal mechanism transfer).
    • Incorporating causal graphical knowledge into predictive modeling (causal-graph data augmentation).
  • Machine learning for social sciences / natural sciences.
    • Recovering data from ceiling effects, a.k.a. censoring: clipped matrix completion.
  • Machine learning methodology in general.
    • Examples: classification learning from limited information (positive-unlabeled classification), robust approximate Bayesian computation, density ratio estimation, and representation power of invertible neural networks.

CV 🔗

My CV can be found here.

Contacts 🔗

Please find my current email address in the sidebar.

News and Upcoming Events 🔗

1 Apr 2022

Joined Recruit Co., Ltd. as a Data Scientist!

24 Mar 2022

Received Ph.D. in Science from the University of Tokyo!

8 Mar 2022

Our collaboration work (led by Masahiro Fujisawa) has been awarded IBIS 2021 Outstanding Presentation Award!

13 Jan 2022

Organizing a special session at StatsML Sypmposium'21 (Feb. 9-11 JST). I'm also running a count-down article event. Please join us!

10-12 Nov 2021

Presenting our work at IBIS 2021! On causal-graph data augmentation (No.66) on 12th Nov, and our collaborative work on 10th Nov (No.4) and 11th Nov (No.78).

Older news are archived here.