Takeshi Teshima, Ph.D.

Hi! I’m Takeshi Teshima. I’m a Data Scientist at Recruit Co., Ltd. and researcher in machine learning.

Previously, I received Ph.D. in Science (machine learning) from the University of Tokyo in 2022 (advisor: Professor Masashi Sugiyama, Graduate School of Frontier Sciences) 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 🔗

20 Jan 2023

I have received the certificate of "NIPPON COCORO ACTION" Certified Supporter.

4 Mar 2023

I'll be honored to give a talk at JSS2023Spring on causal mechanism transfer. Our session will be PM-A (14:05~15:45 @ 1F Room 120 and Zoom A).

28 Nov - 1 Dec 2022

I'll be at the ICDM conference to be held in Orlando, FL, USA!

19 Nov 2022

I will be taking part in a research mentoring session at IBIS2022!

01 Oct 2022

Our book chapter "Rethinking Importance Weighting for Transfer Learning" has been published as part of Federated and Transfer Learning!

Older news are archived here.