About

I am a Research Fellow at the Digital Medicine Lab. My research develops statistical and machine-learning methodology for trustworthy learning and decision-making from heterogeneous, distributed, incomplete, and privacy-sensitive data.

Major areas include transfer learning, federated learning and inference, Shapley value-based interpretability, missing data, and algorithmic fairness, with applications to healthcare and other high-stakes real-world systems.