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, advised by Prof. Le Song. My other interests include feature engineering over graphs, interpretable ML, and healthcare ML problems.

I previously worked at Astound as a Data Scientist, where I built customer ML models and developed model prototyping frameworks. My research was in human-in-the-loop learning, to correct a large number mislabeled text data used for classification by a neural network, while minimizing the number of re-annotations needed.

I completed my undergraduate degrees in computer science and applied statistics at Purdue Univeristy in 2017. At Purdue I researched deep learning techniques for advertisement click through rates under Prof. Xiao Wang. This was possible through an grant that supported undergraduate research which was led by Prof. Mark Daniel Ward.