I’m a research scientist at CyberAgent, Inc.

My research interest is the intersection of Machine Learning and Economics(not only Causal Inference!). Especially, I am interested in the sampling/selection bias in the real-world application. Also, I am interested in how we can combine Mechanism Design, Causal Inference, and Machine Learning.

Research Topics

• Counterfactual Machine Learning
  • Off-Policy Evaluation/Learning
• Machine Learning for Causal Inference
  • ITE Prediction
  • Uplift Modeling
• Causal Inference
  • Distributional Treatment Effect
• Computational Advertising
  • Delayed Feedback
  • Advertising Auction

Recent Update

• 2024.09.22: Our paper “LLM-based Recommendation in Content Promotion: Empirical Evidence from an ABEMA Field Experiment” has been accepted to CODE@MIT’24!
• 2024.05.02: Our paper “Estimating Distributional Treatment Effects in Randomized Experiments: Machine Learning for Variance Reduction” has been accepted to ICML’24
• 2023.09.29: Our paper “Distributional Treatment Effects of Content Promotion: Empirical Evidence from an ABEMA Field Experiment” has been accepted to CODE@MIT’23!
• 2023.05.09: We translated “Causal Inference: The Mixtape” into Japanese! amazon.jp link
• 2022.05.19: Our paper “Delayed Feedback Modeling with a Time Window Assumption” has been accepted to KDD’22!
• 2021.07.07: Our paper “The Adaptive Doubly Robust Estimator for Policy Evaluation in Adaptive Experiments and a Paradox Concerning Logging Policy” has been accepted to NeurIPS’21.
• 2021.07.07: Our paper “Debiased Off-Policy Evaluation for Recommendation Systems” has been accepted to RecSys’21.
• 2020.09.26: Our paper “Off-Policy Evaluation and Learning for External Validity under a Covariate Shift” has been accepted to NeurIPS’20.
• 2020.06.01: Our paper “Counterfactual Cross-Validation: Stable Model Selection Procedure for Causal Inference Models” has been accepted to ICML’20.
• 2020.04.23: Our paper “ Dual Learning Algorithm for Delayed Conversions” has been accepted to SIGIR’20.
• 2020.1.18: I wrote an introductory level Causal Inference/Econometrics text book and now it is on sale! amazon.jp link
• 2020.1.10: Our paper “A Feedback Shift Correction in Predicting Conversion Rates under Delayed Feedback” has been accepted to The web conference 2020!
• 2019.10.21: Our papers “Dual Learning Algorithm for Delayed Feedback in Display Advertising” and “Unbiased Pairwise Learning from Implicit Feedback” have been accepted to CausalML Workshop at NeurIPS’19.
• 2019.8.20: Our paper “Counterfactual Cross Validation” has been accepted to REVEAL Workshop at RecSys’19.
• 2019.8.20: Our paper “Reinforcement Learning meets Double Machine Learning” has been accepted to REVEAL Workshop at RecSys’19.
• 2018.12.4: Our paper “Efficient Counterfactual Learning from Bandit Feedback” has been accepted to AAAI 2019!