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Yichen Zhang joined Purdue University in 2020 after earning a Ph.D. in Statistics and Operations Research from the Stern School of Business at New York University. He also holds bachelor's degrees in Mathematics and Economics from Peking University, obtained in 2015. Yichen's research primarily focuses on statistical inference for online streaming data, bandits, and reinforcement learning. He is also interested in distributed learning, multi-task learning, and transfer learning, as well as frequency-domain time series analysis with applications in supply chains. His work on nonsmooth optimization statistical models has been published in reputable journals including the Annals of Statistics, the Journal of the American Statistical Association, Operations Research, Mathematics of Operations Research, Machine Learning, and Stochastic Processes Applications. In addition, Yichen serves as an Associate Editor for the Journal of Computational and Graphical Statistics.
GRE is optional.