About Me

I am a final-year Ph.D. student in the Department of Statistics at Purdue University, advised by Jennifer Neville. I have also worked closely with Vinayak Rao, Qiang Liu, and Petros Drineas.
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.

My general research area is statistical machine learning. In particular, my research interests include kernel methods for hypothesis testing, approximate Bayesian inference (MCMC and variational methods), statistical models for network data, and randomized sketching algorithms. Previously, I have worked on nonparametric goodness-of-fit tests for discrete distributions, point-process models for dynamic networks, graph sampling algorithms, and ensemble methods for collective classification.

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