About me. 

I am currently a postdoctoral research fellow in the Department of Statistics at Harvard University, starting in September 2019.  My advisor is Prof. Susan A. Murphy Prior to joining Harvard University, I received Doctoral degree in Statistics from the University of Michigan and Bachelor’s degree in Statistics from Sun Yat-Sen University (Zhongshan University).   


My research focuses on sequential decision-making problems with applications in mobile health. In particular, I work on developing
  • new experimental designs (micro-randomized trial, MRT) for use in mobile health 
  • off-line/batch data analysis methods using data collected from MRT (causal inference, policy evaluation/learning)
  • online Reinforcement Learning algorithms that sequentially select interventions based on past history with the goal to maximize the long-term outcomes.  


  • 2014 - 2019: Ph.D in Statistics, University of Michigan, Ann Arbor, MI, United States.
  • 2009 - 2013: B.S. in Statistics, School of Mathematics and Computational Science, Sun Yat-Sen University, Guangzhou, P.R.China.

Selected Publications

[1] Liao, P., Klasnja, P., Tewari, A. and Murphy, S.A., 2016. Sample size calculations for micro‐randomizedtrials in mHealth. Statistics in medicine, 35(12), pp.1944-1971.  (An online sample size calculator could be assessed here (see more). The online calculator may not be accessible due to high traffic. Please download the R package instead.)

[2]  Liao, P., Dempsey, W., Sarker, H., Hossain, S.M., al'Absi, M., Klasnja, P. and Murphy, S., 2018. Just-in-Time but Not Too Much: Determining Treatment Timingin Mobile Health. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT), 2(4), p.179.

[3] Dempsey, W., Liao, P., Kumar, S. and Murphy, S.A., 2020. The stratified micro-randomized trial design: sample size considerations for testing nested causal effects of time-varying treatments. Annals of Applied Statistics, Vol. 14, No.2, 661-684.

[4] Tomkins, S., Liao, P., Yeung, S., Klasnja, P., and Murphy, S.A., 2019. Intelligent Pooling in Thompson Sampling for RapidPersonalization in Mobile Health. Reinforcement Learning for Real Life ICML 2019 Workshop 

[5] Liao, P., Greenewald, K., Klasnja,P., and Murphy, S.A., 2020 PersonalizedHeartSteps: A Reinforcement Learning Algorithm for Optimizing PhysicalActivity.  Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT) .

Work in Progress
[1] Liao, P., Klasnja, P., and Murphy, S.  Off-Policy Estimation of Long-Term Average Outcomes with Applications to Mobile Health. Minor revision. Journal of the American Statistical Association.  

  • Email: pengliao at g dot harvard dot edu
  • Address: 316.02 Science Center, 1 Oxford St, Cambridge, MA 02138