I’m a first year PhD student at NYU Courant (currently remote in Seattle, WA), broadly interested in the intersection of applied mathematics, machine learning, and scientific computing. I am especially interested in problems related to data driven control, model based RL, and applied mathematics for practical problems. On the more practical side, I am interested in working with GPU accelerated computational routines, see my github for some examples of recent projects.
Previously, I worked for three years as a Senior Software Engineer at Applied Predictive Technologies on statistical modeling pipelines. At APT, I provided technical and team leadership on a team of four, mentored multiple junior teammates, led or co-led a few research investigations, co-led APT’s Cornell recruiting efforts, and helped contribute to a range of diversity initiatives.
I graduated Phi Beta Kappa from Cornell University in May 2017. I received a B.A. in Mathematics (cum laude), a B.A. in Computer Science, and was a Tanner Dean’s Scholar. I spent most of my time outside class doing research. I worked with Siddhartha Banerjee for about a year on randomized personal PageRank algorithms to solve sparse matrix equations, and for a year and a half in Jesse H. Goldberg’s computational neuroscience lab studying mammalian motor control.