Students

Current Ph.D. Students

• Haozhen Yu
• Zhenbang Jiao
• Xuerong Wang

Alumni

• Steve Dignan, MS, 2024
  A Comparison of Logistic PCA and Selected Data Embedding Procedures for Binary Data with Application to Breast Cancer and Glioblastoma Data
• Lun Li, Ph.D., 2024
  A Quasi-Likelihood Approach to Latent Space Modeling for Compositional Data: Computation, Model Diagnostics, and Applications
  Now at FDA, Division of Oncology, Silver Spring, MD.
• Ruochen Huang, Ph.D., 2023
  Enhancing Exponential Family PCA: Statistical Issues and Remedies
  Now Quantitative Analytics Specialist at Wells Fargo, Dallas, TX.
• Bo Luan, Ph.D., 2022 (Whitney Research Award Winner, co-advised with Yunzhang Zhu)
  Model Complexity in Linear Regression: Extensions for Prediction and Heteroscedasticity
  Now at Google, Mountain View, CA.
• Jianhao Zhang, Ph.D., 2021
  Learning from Binary Matrix and Tensor Data with Sparsity
• Jiae Kim, Ph.D., 2020 (co-advised with Steve MacEachern)
  Nonlinear Generalizations of Linear Discriminant Analysis: the Geometry of the Common Variance Space and Kernel Discriminant Analysis
  Now Visiting Assistant Professor, Department of Statistics, Indiana University, IN.
• Shanshan Tu, Ph.D., 2019 (co-advised with Yunzhang Zhu)
  Case Influence and Model Complexity in Regression and Classification
  Now Data Scientist at Latitude AI, CA.
• Tayler Blake, Ph.D., 2018
  Nonparametric Covariance Estimation for Longitudinal Data
  Now at Root Insurance, Columbus, OH.
• Liubo Li, Ph.D., 2017 (co-advised with Vince Vu)
  Trend-Filtered Projections for Principal Component Analysis
  Now at ZestFinance, Los Angeles, CA.
• Jieyi Jiang, Ph.D., 2017 (co-advised with Steve MacEachern)
  Realistic Predictive Risk: The Role of Penalty and Covariate Diffusion in Model Selection
  Now at Amazon, Seattle, WA.
• Andrew Landgraf, Ph.D., 2015 (Whitney Research Award Winner)
  Generalized Principal Component Analysis: Dimensionality Reduction through the Projection of Natural Parameters
  Now Data Scientist at Root Insurance, Columbus, OH.
• John Lewis, Ph.D., 2014 (Craig Cooley Memorial Prize Winner, co-advised with Steve MacEachern)
  Bayesian Restricted Likelihood Methods
  Now at Upstart, Columbus, OH.
• Zhiyu Liang, Ph.D., 2014
  Eigen-Analysis of Kernel Operators for Nonlinear Dimension Reduction and Discrimination
  Now Principal ML/AI Engineer at Nike, San Francisco, CA.
• Rui Wang, Ph.D., 2012
  Comparisons of Classification Methods in Efficiency and Robustness
  Now at Nationwide Insurance, Columbus, OH.
• Kazuki Uematsu, Ph.D., 2012
  Statistical Consistency of Ranking: Bipartite and Multipartite Cases
  Now at Vendor Service Co., Tokyo, Japan.
• Cong Liu, Ph.D., 2012 (co-advised with Tao Shi)
  Two Tales of Variable Selection for High Dimensional Data: Screening and Model Building
  Now at American Express, New York, NY.
• Yoonsuh Jung, Ph.D., 2010 (co-advised with Steve MacEachern)
  Regularization of Case Specific Parameters: A New Approach for Improving Robustness and/or Efficiency of Statistical Methods
  Now Professor, Department of Statistics, Korea University, Korea.
• Youlan Rao, Ph.D., 2009 (co-advised with Jason Hsu)
  Statistical Analysis of Microarray Experiments in Pharmacogenomics
  Now at United Therapeutics, Research Triangle Park, NC.
• Yonggang Yao, Ph.D., 2008 (Whitney Research Award Winner)
  Statistical Applications of Linear Programming for Feature Selection via Regularization Methods
  Now Research Statistician/Software Developer, STAT Group at SAS Institute, Cary, NC.
• Zhenhuan Cui, Ph.D., 2007 (SAS Summer Fellowship Recipient)
  The Solution Paths of Multicategory Support Vector Machines: Algorithm and Applications
  Now Research Statistician, Enterprise Miner R & D department at SAS Institute, Cary, NC.
• List of Students in Mathematics Genealogy