ML@GT - CODA S1125H

Atlanta, GA 30308

I am currently a machine learning Ph.D. student at Georgia Tech. My research is in the intersection of deep learning and symbolic reasoning to enable label efficient and interpretable learning. The problem domains I work are across vision, text, and time series domains. I am advised by Prof. Irfan Essa and also work closely with Prof. Le Song and Prof. Mayur Naik. My other interests include feature engineering over graphs, interpretable ML, and healthcare ML problems.

During my summers I am fortunate to have internship opportunties so far at Amazon and at IBM Research. I previously worked at Astound as a Data Scientist, where researched and developed human-in-the-loop learning systems.

I completed my undergraduate degrees in computer science and applied statistics at Purdue Univeristy in 2017, where I was advised by Prof. Xiao Wang and Prof. Mark Daniel Ward.