| 2025 | ICML | Log-Sum-Exponential Estimator for Off-Policy Evaluation and Learning. | Armin Behnamnia, Gholamali Aminian, Alireza Aghaei, Chengchun Shi, Vincent Y. F. Tan, Hamid R. Rabiee |
| 2025 | ICML | Unraveling the Interplay between Carryover Effects and Reward Autocorrelations in Switchback Experiments. | Qianglin Wen, Chengchun Shi, Ying Yang, Niansheng Tang, Hongtu Zhu |
| 2025 | ICML | Demystifying the Paradox of Importance Sampling with an Estimated History-Dependent Behavior Policy in Off-Policy Evaluation. | Hongyi Zhou, Josiah P. Hanna, Jin Zhu, Ying Yang, Chengchun Shi |
| 2025 | ICML | Balancing Interference and Correlation in Spatial Experimental Designs: A Causal Graph Cut Approach. | Jin Zhu, Jingyi Li, Hongyi Zhou, Yinan Lin, Zhenhua Lin, Chengchun Shi |
| 2024 | AISTATS | Robust Offline Reinforcement Learning with Heavy-Tailed Rewards. | Jin Zhu, Runzhe Wan, Zhengling Qi, Shikai Luo, Chengchun Shi |
| 2024 | ICML | Combining Experimental and Historical Data for Policy Evaluation. | Ting Li, Chengchun Shi, Qianglin Wen, Yang Sui, Yongli Qin, Chunbo Lai, Hongtu Zhu |
| 2023 | AISTATS | Conformal Off-Policy Prediction. | Yingying Zhang, Chengchun Shi, Shikai Luo |
| 2023 | AISTATS | Optimizing Pessimism in Dynamic Treatment Regimes: A Bayesian Learning Approach. | Yunzhe Zhou, Zhengling Qi, Chengchun Shi, Lexin Li |
| 2023 | CogSci | A generalized method for dynamic noise inference in modeling sequential decision-making. | Jing-Jing Li, Chengchun Shi, Lexin Li, Anne G. E. Collins |
| 2023 | ICML | A Reinforcement Learning Framework for Dynamic Mediation Analysis. | Lin Ge, Jitao Wang, Chengchun Shi, Zhenke Wu, Rui Song |
| 2023 | ICML | A Robust Test for the Stationarity Assumption in Sequential Decision Making. | Jitao Wang, Chengchun Shi, Zhenke Wu |
| 2023 | ICML | An Instrumental Variable Approach to Confounded Off-Policy Evaluation. | Yang Xu, Jin Zhu, Chengchun Shi, Shikai Luo, Rui Song |
| 2023 | KDD | DNet: Distributional Network for Distributional Individualized Treatment Effects. | Guojun Wu, Ge Song, Xiaoxiang Lv, Shikai Luo, Chengchun Shi, Hongtu Zhu |
| 2022 | ICML | A Minimax Learning Approach to Off-Policy Evaluation in Confounded Partially Observable Markov Decision Processes. | Chengchun Shi, Masatoshi Uehara, Jiawei Huang, Nan Jiang |
| 2021 | ICML | Deeply-Debiased Off-Policy Interval Estimation. | Chengchun Shi, Runzhe Wan, Victor Chernozhukov, 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 |