Qingyang Xu, PhD
Welcome! I'm currently a senior AI engineer at LinkedIn. Previously, I have worked as an AI engineer at Meta, DoorDash, and Helm.ai.
I received my Ph.D. in Operations Research at MIT in 2022, where I am fortunate to be advised by Professor Andrew W. Lo, and my undergraduate degree from Stanford.
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.
Estimating Correlations Between Clinical Trial Outcomes Using Generalised Estimating Equations. Oxford Bulletin of Economics and Statistics (2025)
Identifying and Mitigating Potential Biases in Predicting Drug Approvals. Drug Safety (2022)
Accelerating Glioblastoma Therapeutics via Venture Philanthropy, Drug Discovery Today (2021)
Bayesian Adaptive Clinical Trials for Anti‐Infective Therapeutics during Epidemic Outbreaks. Harvard Data Science Review (2020)