Was a postdoctoral scholar at the University of California, Berkeley, working on asymptotic theory for network models and the nonparametric bootstrap for big data.
Education
PhD from the Machine Learning Department at Carnegie Mellon University, focusing on analyzing theoretical properties of different proximity measures arising from random walks and using them for designing fast algorithms. Undergraduate from the Computer Science and Engineering Department at the Indian Institute of Technology, Kharagpur.
Background
Associate professor of Statistics at the University of Texas at Austin. Works in the intersection of high-dimensional statistics, optimization, and Machine Learning theory. Co-PI in EnCORE: Institute for Emerging CORE Methods of Data Science and affiliated with the AI institute. Also a GSC member of Computer Science and Operations Research and Industrial Engineering.