I am an assistant professor in the Elmore Family School of Electrical and Computer Engineering at Purdue University. I lead the Probabilistic and Understandable Machine Learning Lab. My research interests are in machine learning focused on the fundamentals of distribution alignment, probabilistic models, and explainable AI. More recently, I have focused on the fundamentals of distribution alignment including new algorithms, metrics, and applications such as causality and domain generalization. On the explainable AI side, I am interested in explaining distribution shifts and tractable uncertainty quantification. Previously, I was a postdoc at Carnegie Mellon University working with Prof. Pradeep Ravikumar. I completed my Computer Science PhD at The University of Texas at Austin in 2017 advised by Prof. Inderjit Dhillon and Prof. Pradeep Ravikumar. I was awarded the NSF Graduate Research Fellowship (NSF GRFP).
PostDoc in Machine Learning, 2019
Carnegie Mellon University
PhD in Computer Science, 2017
The University of Texas at Austin
MS in Computer Science, 2015
The University of Texas at Austin
BS in Electrical Engineering, 2012
Georgia Institute of Technology
BA in Natural Sciences, 2011
Covenant College