Biography (CV)

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I am currently an Assistant Professor of Information, Operations and Management Sciences at Stern School of Business at New York University.

Before joining NYU Stern, I did a postdoc with Professor Michael I. Jordan at the University of California, Berkeley. I earned my doctoral degree from the Machine Learning Department at the School of Computer Science at Carnegie Mellon University. My doctoral dissertation, entitled Learning with Sparsity: Structures, Optimization and Applications, was directed by the committee members: Dr. Jaime Carbonell, Dr. Tom Mitchell, Dr. Larry Wasserman, and Dr. Robert Tibshirani (from Stanford). During my Ph.D., I did internships at Microsoft Research Redmond, IBM T.J. Watson Research Center and NEC Lab America.

Before that, I obtained my master of science in Industry Administration (Operations Research) from the ACO (algorithms, combinatorics and optimization) program in the Tepper School of Business at Carnegie Mellon. My master's work is advised by Prof. Manuel Blum.

I was featured in Forbes 30 under 30 in Science and received the Adobe Data Science Research Award, Google Faculty Research Award, Simons-Berkeley Research Fellowship, and IBM Ph.D. Fellowship.

Research Interests

  • Statistical Inference for Big Data: Inference for Online Data (using Stochastic Gradient Descent), Distributed Data, and High-dimensional Data.
  • Nonparametric Estimation and Shape-restricted Estimation
  • Sequential Analysis and Multi-armed Bandit Learning with Applications to Rank Aggregation, Crowdsourcing, and Revenue Management.
  • Optimization: Non-convex Optimization, Online Stochastic Optimization, and Robust Optimization for Deep Learning
  • Discrete Optimization with Applications to Optimal Network Design in Process Flexibility
  • Please see my publications or Google Scholar profile for more details


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