I am interested in sequential and adaptive decision-making from a statistical perspective, encompassing the areas of adaptive experimentation, reinforcement learning, longitudinal data analysis, and causal inference. I apply these methods to various fields, such as personalized health interventions, online experimentation, pricing and auctions. Additionally, I am interested in nonparametric and semiparametric statistics, high-dimensional statistics, and distributed statistical learning.
My research is partially supported by NSF Grant DMS-2515285 (sole PI).
Hao Yan, Heyan Zhang, Yongyi Guo. Learning with Incomplete Context: Linear Contextual Bandits with Pretrained Imputation. International Conference on Artificial Intelligence and Statistics (AISTATS), 2026.
Yongyi Guo, Ziping Xu. Statistical Inference for Misspecified Contextual Bandits.
Ruiyang Lin, Yongyi Guo, Kyra Gan. Optimal Adjustment Sets for Nonparametric Estimation of Weighted Controlled Direct Effect. Conference on Neural Information Processing Systems, 2025.
Esmaeil Keyvanshokooh, Kyra Gan, Yongyi Guo, Xueqing Liu, Susan A. Murphy. Learning When to Nudge: A Dual-Agent Bandit Framework for Behavioral Interventions.
Susobhan Ghosh, Yongyi Guo, Pei-Yao Hung, Lara Coughlin, Erin Bonar, Inbal Nahum-Shani, Maureen Walton, Susan Murphy. MiWaves Reinforcement Learning Algorithm. Technical report, 2024.
Susobhan Ghosh, Yongyi Guo, Pei-Yao Hung, Lara Coughlin, Erin Bonar, Inbal Nahum-Shani, Maureen Walton, Susan A. Murphy. reBandit: Random Effects based Online RL algorithm for Reducing Cannabis Use. AI for Social Good Track, International Joint Conference on Artificial Intelligence (IJCAI), 2024.
Yongyi Guo, Ziping Xu, Susan A. Murphy. Online Learning in Bandits with Predicted Context. International Conference on Artificial Intelligence and Statistics (AISTATS), 2024.
Ivana Malenica, Yongyi Guo, Kyra Gan, Stefan Konigorski. Anytime-valid Inference in N-of-1 Trials. Proceedings of the 3rd Machine Learning for Health Symposium, PMLR 225:307-322, 2023.
Jianqing Fan, Yongyi Guo, Maxine Yu. Policy Optimization Using Semi-parametric Models for Dynamic Pricing. Journal of the American Statistical Association (2022): 1-37.
Yongyi Guo, Dominic Coey, Mikael Konutgan, Wenting Li, Chris Schoener, Matt Goldman. Machine Learning for Variance Reduction in Online Experiments. Conference on Neural Information Processing Systems, 2021.
Yongyi Guo†, Ziwei Zhu†, Jianqing Fan. Best subset selection is robust against design dependence. [†: equal contribution]
Jianqing Fan, Yongyi Guo, Kaizheng Wang. Communication-Efficient Accurate Statistical Estimation. Journal of the American Statistical Association (2021): 1-11.
Jianqing Fan, Yongyi Guo, Bai Jiang. Adaptive Huber Regression on Markov Dependent Data. Stochastic Processes and their Applications 150 (2022): 802-818.
Yongyi Guo, Zhiyi You, Min Qian, Hao Ge. Stochastic Robustness and Relative Stability of Multiple Pathways in Biological Networks. Science China Mathematics 2017, 47:1831 – 1852. (Winner of Excellent Paper Award)
Susobhan Ghosh, Pei-Yao Hung, Lara N Coughlin, Erin E Bonar, Yongyi Guo, Inbal Nahum-Shani, Maureen Walton, Mark W Newman, Susan A. Murphy. "It felt more real": Investigating the User Experience of the MiWaves Personalizing JITAI Pilot Study. EAI Pervasive Health 2025.
Anna L. Trella, Susobhan Ghosh, Erin E. Bonar, Lara Coughlin, Finale Doshi-Velez, Yongyi Guo, Pei-Yao Hung, Inbal Nahum-Shani, Vivek Shetty, Maureen Walton, Iris Yan, Kelly W. Zhang, Susan A. Murphy. Effective Monitoring of Online Decision-Making Algorithms in Digital Intervention Implementation.
Coughlin, L.N., Campbell, M., Wheeler, T., Rodriguez, C., Florimbio, A.R., Ghosh, S., Guo, Y., Hung., P., Zhang, K.W., Zimmerman, L., Bonar, E.E., Walton, M.A., Murphy, S., Nahum-Shani, I. A mobile health intervention for emerging adults with regular cannabis use: A micro-randomized pilot trial design protocol. Contemporary Clinical Trials 145 (2024): 107667.
Asim H. Gazi, Yongyi Guo, Daiqi Gao, Ziping Xu, Kelly W. Zhang, Susan A. Murphy. Statistical Reinforcement Learning in the Real World: A Survey of Challenges and Future Directions.
Asim H. Gazi, Susobhan Ghosh, Yongyi Guo, Daiqi Gao, Ziping Xu, Inbal Nahum-Shani, Susan A. Murphy. Key Concepts In Online Learning And Decision Making For Just-In-Time Adaptive Interventions.