Advisors: Ce Zhang, Tian Li
I am currently a Postdoctoral Scholar co-advised by Ce Zhang and Tian Li. I received my Ph.D. in Computer Science from the University of Maryland, College Park in May 2024 and was advised by Furong Huang. While at UMD, I was an NSF COMBINE Fellow and RSA Security Scholar (2024). Prior to joining the University of Chicago, I spent a year at Yale University (2024-2025) as a Postdoctoral Research Associate within the Hoon Cho and LiGHT labs where I researched applications of AI/ML to pharmaceutical and clinical settings.
I obtained my BA in Mathematics from the University of Virginia (2015). I was born and raised in Richmond, VA.
Machine learning models and training data continue to grow without bound. However, smaller networks and faster learning strategies improve technological equity, enable deployment on the edge, reduce computational/memory costs, and help alleviate negative environmental impacts. Simultaneously, we must limit the extent to which these systems train over sensitive user data. This motivates much of my research, which lives at the intersection of efficiency and privacy.
