About Me

I am a final-year Ph.D. student in the Department of Statistics at Purdue University, advised by
Prof. Jennifer Neville in the Departments of Computer Science and Statistics. I am also fortunate to have collaborated with Profs. Vinayak Rao, Petros Drineas, and Qiang Liu.

My general research interests lie at the intersection of machine learning, statistics, data mining, and theoretical computer science. More specifically, my current interests include statistical network analysis, point processes, kernel and nonparametric methods, Stein's method, approximate Bayesian inference, and randomized sketching methods. Motivated by the analysis of large-scale datasets exhibiting complex dependencies, my research focuses on developing interpretable models for relational and temporal data, flexible model criticism techniques for intractable distributions, and scalable learning algorithms with provable guarantees.

I obtained a joint M.S. degree in Statistics and Computer Science from Purdue University in 2015, and a B.S. degree in Statistics from the Special Class for the Gifted Young at the University of Science and Technology of China in 2013.

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