Biography

I have recently joined the School of Electrical and Computer Engineering at Purdue University.

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 obtained my B.S. in Electrical Engineering from Georgia Institute of Technology with a minor in Computer Science. I was awarded the NSF Graduate Research Fellowship (NSF GRFP).

My research interests focus on the fundamentals of machine learning, probabilistic models, unconventional deep learning and explainable AI with an emphasis on density estimation. Currently, I am focused on creating the foundations for destructive deep learning, which is a modular learning approach to deep learning similar in concept to reverse engineering patterns in data. I am also interested in explainable AI techniques both from an intrinsic viewpoint by creating more interpretable methods (e.g., via destructive learning) or from an extrinsic viewpoint by creating diagnostic methods to better understand models—e.g., what would the model predict if the input was changed in interesting ways?