top of page

Qingyang Xu, PhD

  • Liknedin
  • Google Scholar
  • RG Icon


I received my Ph.D. in Operations Research at MIT in 2022, where I am fortunate to be advised by Professor Andrew W. Lo.


After graduation, I worked as machine learning scientist at Meta (Facebook),, and (currently) DoorDash.

Research Interests

I am broadly interested in developing advanced techniques in machine learning, statistics and optimization to facilitate the discovery and clinical testing of novel therapeutics.


In particular, I am interested in (1) applying artificial intelligence to predict clinical trial outcomes, (2) optimizing the clinical trial design using multi-armed bandit and reinforcement learning techniques, and (3) devising novel financial strategies to reduce the financial risk of early-stage biomedical investments.



Xu et al. (2022) "Identifying and Mitigating Potential Biases in Predicting Drug Approvals", Drug Safety (link)

Siah et al. (2021) "Accelerating Glioblastoma Therapeutics via Venture Philanthropy", Drug Discovery Today (link)

Chaudhuri et al. (2020) "Bayesian Adaptive Clinical Trials for Anti‐Infective Therapeutics during Epidemic Outbreaks", Harvard Data Science Review (link)

bottom of page