Here are the archives of (relatively) important news:
[2025.11, updates] I have become a Ph.D. candidate (and received M.S. from Cornell CS)! I look forward to the upcoming journey in the rest of my PhD program, and I'm grateful for the kind support from my amazing advisors, committee, collaborators, and also financial support from the Funai Overseas Scholarship and the Quad Fellowship.
[2025.10, lecture, resource] I gave a guest lecture at the ML in feedback systems class at Cornell (CS6784) and released the video recording here. I talked about the intro of off-policy evaluation and learning (OPE/L) and my own research related to OPE/L and ML in feedback systems. Check it out!
[2025.08, updates, fellowship] I have been selected as a Quad fellow for the 2025-2026 academic year (cohort 3, as a Japan fellow). I appreciate the financial support from them for my third year at Cornell, and look forward to interacting with the other fellows!
[2025.07, paper] Our paper "An Off-Policy Learning Approach for Steering Sentence Generation towards Personalization" has been accepted to RecSys2025. See you in Prague!
[2025.06, updates] I joined the Meta Central Applied Science (CAS) team as a student research intern. See you in San Francisco!
[2025.04, paper] Our paper "Policy Design for Two-sided Platforms with Participation Dynamics" has been accepted to ICML2025. This paper was also featured by AIhub. See you in Vancouver!
[2024.07, paper] Our paper "Effective Off-Policy Evaluation and Learning in Contextual Combinatorial Bandits" has been accepted to RecSys2024. See you in Bari!
[2024.01, paper] Our paper "Off-Policy Evaluation of Slate Bandit Policies via Optimizing Abstraction" has been accepted to WebConf2024. See you in Singapore!
[2024.01, paper] Our paper "Towards Assessing and Benchmarking Risk-Return Tradeoff of Off-Policy Evaluation" has been accepted to ICLR2024. This paper was also featured by the TokyoTech news. See you in New Orleans!
[2023.11, paper, open-source] Our twin papers: "Towards Assessing and Benchmarking Risk-Return Tradeoff of Off-Policy Evaluation" (link) and "SCOPE-RL: A Python Library for Offline Reinforcement Learning and Off-Policy Evaluation" (link) are now on arXiv! We present a new evaluation metric and open-source software (GitHub, PyPI, readthedocs) for OPE. Feel free to star and folk!
[2023.09, paper] Our paper "Future-Dependent Value-Based Off-Policy Evaluation in POMDPs" has been accepted to NeurIPS2023. See you in New Orleans!
[2023.08, updates, fellowship] I joined the Cornell CS Ph.D. program. I appreciate the financial support of the Funai Overseas Scholarship for the first two academic years. Looking forward to my new journey at Cornell!
[2023.05, paper] Our paper "Off-Policy Evaluation of Ranking Policies under Diverse User Behavior" has been accepted to KDD2023. See you in Long Beach!
[2023.03, updates, award] I graduated from Tokyo Institute of Technology with a B.Eng (Industrial Engineering and Economics) and honor of Excellent Student Award! I am grateful for all the amazing people I met and the wonderful opportunities I could have during my undergraduate study.
[2022.11, paper] Our paper "Policy-Adaptive Estimator Selection for Off-Policy Evaluation" has been accepted to AAAI2023. See you in Washington DC!
[2022.02, paper, award] Our paper "Doubly Robust Off-Policy Evaluation for Ranking Policies under the Cascade Behavior Model" has been honored as one of the Best Paper Award Runner-Ups at WSDM2022! I really appreciate and congratulate all my co-authors.
[2021.07, paper] Our paper "Evaluating the Robustness of Off-Policy Evaluation" has been accepted to RecSys2021. See you in Amsterdam!
[2021.02, open-source] We publicized awesome-offline-rl repository and collect papers about Offline RL and OPE. Check it out!