Welcome
Hello, my name is Yanjie Zhong, a PhD candidate in statistics, advised by Professor Todd Kuffner and Professor Soumendra Lahiri.
EDUCATION
Ph.D. in Statistics, Washington University in St. Louis, 2018 – 2023 (expected)
B.S. in Probability and Statistics, Peking University, China, 2014 – 2018
RESEARCH INTEREST
Resampling Methods, Dependent Data, Missing Data, Statistical Inference, High Dimensional Statistics, Numerical Optimization
TEACHING
- MEC 537: Data Analysis Graduate Teaching Assistant Fall 2018
- MATH 2200: Probability and Statistics Assistant Instructor Fall 2019
- DAT 537: Data Analysis Graduate Teaching Assistant Fall 2019
- MATH 2200: Probability and Statistics Assistant Instructor Spring 2020
- DAT 537: Data Analysis Graduate Teaching Assistant Fall 2020
- DAT 537: Data Analysis Graduate Teaching Assistant Spring 2021
- DAT 537: Data Analysis Graduate Teaching Assistant Summer 2021
- MATH 2200: Probability and Statistics Assistant Instructor Fall 2021
- DAT 537: Data Analysis Graduate Teaching Assistant Fall 2021
Research Papers
- Y. Zhong, T. Kuffner and S. Lahiri. Conditional randomization rank test.
- Y. Zhong, T. Kuffner and S. Lahiri. Online bootstrap inference on non-convex SGD estimator.
- Y. Zhong, T. Kuffner and S. Lahiri. On the zeroth-order expectation maximization algorithm.
- Y. Zhong, J. Li and S. Lahiri. Probabilistic analysis of SARAH in non-convex finite sum problem.
- Y. Zhong, J. Li and S. Lahiri. Dimension-free concentration inequalities for vector martingales with subGaussian norm and applications in online learning.
- Z. Wang, Y. Zhong, Z. Ye, L. Zeng, Y. Chen, M. Shi, Z. Yuan, Q. Zhou, M. Qian, M.Q. Zhang (2021). MarkovHC: Markov hierarchical clustering for the topological structure of high-dimensional single-cell omics data with transition pathway and critical point detection. Nucleic Acids Research.