Xueqing Liu 刘雪晴

About

I am a postdoctoral fellow in the Department of Statistics at Harvard University, working with Professor Susan Murphy. My research develops statistical and machine learning methods that make digital health interventions smarter — deciding when, whom, and how to nudge, and measuring whether it worked.

I received my Ph.D. in Biostatistics and Health Data Science from Duke-NUS Medical School, advised by Professor Bibhas Chakraborty. Before that, I earned my Master's and Bachelor's degrees from Peking University.

Research Interests

• Contextual bandits & reinforcement learningOnline decision-making algorithms that personalize treatment in real time.
• Causal inference & longitudinal dataEstimating time-varying treatment effects from intensively collected data.
• Design & analysis of experimentsMicro-randomized trials and adaptive experimental designs for mobile health.
• Just-in-time adaptive interventionsDelivering the right support at the moment it is most likely to help.

News

• 2025Joined the Department of Statistics at Harvard University as a postdoctoral fellow, working with Susan Murphy.

Selected Publications

• Thompson Sampling for Zero-Inflated Count Outcomes with an Application to the Drink Less Mobile Health Study

  Xueqing Liu, Nina Deliu, Tanujit Chakraborty, Lauren Bell, Bibhas Chakraborty

  Annals of Applied Statistics, 2025Journal

• Incorporating Nonparametric Methods for Estimating Causal Excursion Effects in Mobile Health with Zero-Inflated Count Outcomes

  Xueqing Liu, Tianchen Qian, Lauren Bell, Bibhas Chakraborty

  Biometrics, 2024Journal

• Contextual Bandits with Budgeted Information Reveal

  Kyra Gan, Esmaeil Keyvanshokooh, Xueqing Liu, Susan Murphy

  AISTATS, 2024arXiv

Professional Service

Reviewer: Annals of Applied Statistics, Biometrics, Biostatistics, Trials, Statistical Modelling, BMJ Digital Health & AI, npj Digital Public Health.

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