| 2025 | ICML | Zero-Inflated Bandits. | Haoyu Wei, Runzhe Wan, Lei Shi, Rui Song |
| 2025 | WWW | Know When to Fold: Futility-Aware Early Termination in Online Experiments. | Yu Liu, Runzhe Wan, Yian Huang, James McQueen, Doug Hains, Jinxiang Gu, Rui Song |
| 2024 | AAAI | Effect Size Estimation for Duration Recommendation in Online Experiments: Leveraging Hierarchical Models and Objective Utility Approaches. | Yu Liu, Runzhe Wan, James McQueen, Doug Hains, Jinxiang Gu, Rui Song |
| 2024 | AISTATS | Robust Offline Reinforcement Learning with Heavy-Tailed Rewards. | Jin Zhu, Runzhe Wan, Zhengling Qi, Shikai Luo, Chengchun Shi |
| 2023 | AISTATS | Towards Scalable and Robust Structured Bandits: A Meta-Learning Framework. | Runzhe Wan, Lin Ge, Rui Song |
| 2023 | ICML | Multiplier Bootstrap-based Exploration. | Runzhe Wan, Haoyu Wei, Branislav Kveton, Rui Song |
| 2023 | KDD | Experimentation Platforms Meet Reinforcement Learning: Bayesian Sequential Decision-Making for Continuous Monitoring. | Runzhe Wan, Yu Liu, James McQueen, Doug Hains, Rui Song |
| 2022 | ICML | Safe Exploration for Efficient Policy Evaluation and Comparison. | Runzhe Wan, Branislav Kveton, Rui Song |
| 2021 | ICML | Deeply-Debiased Off-Policy Interval Estimation. | Chengchun Shi, Runzhe Wan, Victor Chernozhukov, Rui Song |
| 2021 | KDD | Multi-Objective Model-based Reinforcement Learning for Infectious Disease Control. | Runzhe Wan, Xinyu Zhang, Rui Song |
| 2020 | ICML | Does the Markov Decision Process Fit the Data: Testing for the Markov Property in Sequential Decision Making. | Chengchun Shi, Runzhe Wan, Rui Song, Wenbin Lu, Ling Leng |