I have benefited greatly from the guidance of many outstanding mentors throughout my career. Inspired by my past mentors, I strive to cultivate a warm, friendly, and open intellectual environment. Highly motivated graduate students and undergraduate students are welcome to reach out to me about research projects. Some interest in working on methodology and applications motivated by real data sets and problems from public health, biology, and medicine is a plus. However, I can also supervise students who are primarily interested in statistical theory or other application areas.

I am able to accept PhD students who have passed the Statistics PhD Qualifying Exam (offered annually) at the University of South Carolina. My expectation for PhD students working under my direction is two fully completed projects by the time of graduation. Students interested in pursuing academia should ideally also have a third project in progress when they apply for postdocs and/or faculty positions.

Below are a few of the dissertation topics of my current students:

  • Bayesian methodology and scalable algorithms for “large n, small p” and “large p, small n” problems
  • multivariate statistical methods for unsupervised learning