Biography

I am a Ph.D. student at Johns Hopkins University, where I am fortunate to be advised by Prof. René Vidal. My research interests broadly lie in theoretical machine learning and the foundations of data science in order to obtain provable guarantees for ML algorithms. One particular area of interest is the theory of deep learning, both from an optimization and generalization perspective.

I previously completed my MS in Computer Science at Columbia University, where I was advised by Prof. John Wright, and my BS degree in CS and Math at UT Austin.