Statistical Learning of Differential Equations, Optimal Transport in Biology
I am a fourth-year PhD student at the Massachusetts Institute of Technology (MIT) in the Department of Mathematics co-advised by Prof. Philippe Rigollet and Prof. Jörn Dunkel. I am also part of the Interdisciplinary Doctoral Program in Statistics (IDPS) through the Institute for Data, Systems, and Society (IDSS).
Broadly, my research is on the intersection of statistics and physical applied mathematics. I study how statistical and machine learning algorithms can be used to infer and predict systems governed by ordinary and partial differential equations appearing in biology, chemistry, economics, and other fields. Prior to MIT, I graduated in 2019 from the University of Washington (UW) with a Bachelors of Science in Mathematics and Computer Science where I performed research on network inference methods in the Department of Applied Mathematics under Prof. Nathan Kutz.