Master of Science in CSE, 2017
I work on machine learning research in the Data to Actionable Knowledge (DtAK) lab (dtak.github.io). Currently, I am interested in uncertainty estimation for deep models; more broadly, I am interested in building models with gauranteed properties that align with task-specific desiderata, such as interpretability, risk-awareness, satisfaction of domain-specific constraints. In a previous life I did research in pure math -- my Ph.D. is in Algebraic Topology. At Harvard, I teach in the IACS curriculum, I also supervise undergraduate and masters students in research; students who are interested in research opportunities are welcome to contact me directly.