Before coming to UChicago, I received my Ph.D. and M.S. in Physics from the University of Maryland, where my research focused on hybridizing scientific knowledge-based models with machine learning to accurately forecast high-dimensional chaotic systems. I was also a fellow in the Computation and Mathematics for Biological Networks (COMBINE) NSF NRT program at the University of Maryland.
I am interested in using ideas and techniques from physics and data assimilation to develop accurate and stable ML/AI emulators of terrestrial weather and climate, with a focus towards forecasting and assessing the risk of extreme weather events.