Yongyi Guo

Yongyi Guo serves as an Assistant Professor in the Department of Statistics at the University of Wisconsin-Madison, following a postdoctoral fellowship at Harvard University under Susan A. Murphy.

Her academic foundation includes a Ph.D. in Statistics from Princeton University (2022) advised by Jianqing Fan and a B.S. in Mathematical Sciences from Peking University (2016).

Dr. Guo's research integrates statistical learning with digital health applications, specializing in reinforcement learning for personalized mobile interventions and causal inference methodologies. Her work demonstrates particular expertise in micro-randomized trials for cannabis use reduction, where she developed the MiWaves and reBandit algorithms to optimize just-in-time adaptive interventions through online decision-making frameworks.

Analysis of her publication trends reveals consistent focus on bridging theoretical statistics with health implementation challenges, featuring innovations in anytime-valid inference for N-of-1 trials, communication-efficient distributed estimation, and robust regression techniques for dependent data structures.