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Current PhD Advisees

  • Shijie Wang, PhD candidate (expected 2024)
    Dissertation title: New Deep Learning Approaches to Classical Statistical Problems

  • Zile Zhao, PhD candidate (expected 2024)
    Dissertation topic: Bayesian methods for survival analysis and causal inference

  • Sijian Fan, PhD candidate (expected 2025)
    Dissertation topic: integrating side information in matrix completion and regression models

Other Student Collaborators

(* I am not the primary supervisor of these students)

  • Xin Zhi (PhD candidate in Statistics at the University of South Carolina)
    Research project: Bayesian additive regression trees (BART) for survival analysis

  • Liyan Xiong (PhD student in Biostatistics at the University of South Carolina)
    Research project: statistical methods for computational drug repositioning

  • Dayuan Wang (PhD student in Biostatistics at the University of Florida)
    Research project: statistical methods for computational drug repositioning

Alumni

  • Qingyang Liu (graduate student collaborator, ’22-’23)
    Research project: new approaches to modal regression and Gaussian process regression
    First position: Postdoctoral Fellow, Texas A&M University

  • Anja Zgodic (graduate student collaborator, ’22-’23)
    Research project: scalable Bayesian methodology for linear mixed effects models
    First position: Research Data Scientist, Lubrizol

  • Hung-Tien Huang (undergraduate student collaborator, ’22-’23)
    Research project: explainable reinforcement learning with deep generative models
    First position: PhD student in Computer Science, University of North Carolina-Chapel Hill