Kohsuke Kubota

Data Scientist / Ph.D. Candidate

NTT DOCOMO, INC. / Keio University

About Me

I’m a data scientist at NTT DOCOMO, INC. My research interests include marketing science, Bayesian statistics, causal inference, machine learning, and deep neural network. I’m a Ph.D. Candidate in Economics at Keio University, where I’m fortunate to be advised by Prof. Takahiro Hoshino.

Interests
  • Marketing Science
  • Bayesian Statistics
  • Causal Inference
Education

  • PhD Candidate in Economics

    Keio University

  • Master of Informatics

    Kyoto University

  • Bachelor of Engineering

    Kyoto University

Publications
Kohsuke Kubota, Shonosuke Sugasawa (2025). Causal Inference under Threshold Manipulation: A Bayesian Mixture Approach. In KDD 2025 3rd Workshop on Causal Inference and Machine Learning in Practice.
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Yuki Murakami, Kohsuke Kubota, Takumi Hattori, Keiichi Ochiai (2025). Estimation of Single and Synergistic Treatment Effects under Multiple Treatments with Deep Neural Networks. In KDD 2025 3rd Workshop on Causal Inference and Machine Learning in Practice.
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Kohsuke Kubota, Shonosuke Sugasawa, Keiichi Ochiai, Takahiro Hoshino (2025). Bayesian Time-Varying Meta-Analysis via Hierarchical Mean-Variance Random-effects Models. In Japanese Journal of Statistics and Data Science (Impact Factor = 1.0).
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Kohsuke Kubota, Keiichi Ochiai, Takahiro Hoshino (2025). Causal effect of lottery promotions on post-win payments: Evidence from a large field experiment . In Innovative Marketing (Impact Factor = 1.2, Acceptance Rate = 33%).
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Takumi Hattori, Kohsuke Kubota, Keiichi Ochiai (2025). Wald-Differences-in-Differences Estimation without Individual-Level Treatment Data. In AAAI’25 Workshop on Artificial Intelligence with Causal Techniques.
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Academic Service

Journal Reviewer

  • Asia Pacific Journal of Marketing and Logistics