I am an assistant professor of Statistics at the University of Texas at Austin . My interests are in the intersection of asymptotic statistics, scalable algorithms and networks.
Previously I was a postdoctoral scholar at the University of California, Berkeley, where I worked with Prof. Peter Bickel and Prof. Michael Jordan on asymptotic theory for network models and the nonparametric bootstrap for big data. I got my PhD from the Machine Learning Department at Carnegie Mellon University. My doctoral advisor was Prof. Andrew W. Moore. My thesis research has been aimed at analyzing theoretical properties of different proximity measures arising from random walks, and using them for designing fast algorithms. Here is a link to my thesis.
Before joining Carnegie Mellon, I was an undergraduate at the Computer Science and Engineering Department in the Indian Institute of Technology, Kharagpur, where I spent four years. During my undergraduate years I also worked with Prof. Charles Isbell as a summer intern at Georgia Tech.