I am a Ph.D. candidate in Prof. Jérôme Darbon’s group in the Division of Applied Mathematics at Brown University. My research focuses on the areas of machine learning, optimization, imaging science, and partial differential equations. My Ph.D. dissertation focuses on the development of efficient and robust algorithms for large-scale supervised learning tasks (e.g., regression and classification in machine learning).
Prior to my doctoral studies, I completed my M.Sc. degree in applied mathematics in 2015 from ETH Zürich with Prof. George Haller as my M.Sc. thesis advisor. I completed my B.Sc. degree in applied mathematics and physics in 2013 from McGill University with Prof. Michael C. Mackey as my undergraduate honors thesis advisor.