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About Me

Hi! I am an Assistant Professor in the Math department at Boston College. Before this, I was a Hedrick Assistant Adjunct Professor at UCLA under Andrea BertozziJacob Foster, and Guido Montufar. I obtained my Ph.D. in  Applied and Interdisciplinary Mathematics from the University of Michigan. I won the Peter Smereka Award for the best-applied math thesis. My advisors were Anna C. Gilbert and Raj Rao Nadakuditi. I did my undergraduate studies at Carnegie Mellon University, obtaining a B.S. with double majors in discrete math and computer science.

Understanding the mathematical foundations of machine learning algorithms is crucial. My work has contributed to a better understanding of data's intrinsic geometric and probabilistic structure. This understanding has been applied to design better machine learning algorithms. My current area of focus is the mathematical underpinnings of geometric deep learning, optimization, and generalization.

Current Projects

Here, geometry can play a role in a variety of ways. First, we could be looking at certain subspaces of functions in which the geometry of the subspace is important. Second, we could care about maps that factor through different manifolds. Here, the geometry of the manifold is important. Third, we could restrict our parameters to living in certain spaces. Hence, the geometry of this subspace is important. I am interested in understanding how the geometry affects the inductive bias of the machine learning methods. 

See publications for prior projects. 

If you have any questions or ideas you want to discuss, or if you want to discuss math and computer science, ways to contact me can be found under the contact me tab.