Haiming Zhou

Background

I received a B.S. degree in Statistics from the University of Science and Technology of China (2009), an M.S. in Mathematical Sciences from Clemson University (2012), and a Ph.D. in Statistics from the University of South Carolina (2015). I am currently an associate director at Daiichi Sankyo, Inc. Full CV.

My research interests include survival analysis, Bayesian nonparametrics, clinical trial designs, measurement error models, frequentist nonparametric methods, semiparametric regression, spatial analysis, copulas, statistical computing for large datasets, modal regression, and applications in epidemiology/public health. The Software page includes R packages for implementing my proposed methods. Publications. Google Scholar Profile. ResearchGate Profile.

Call for papers - A special issue of Stats

Survival analysis has a broad range of applications in fields that deal with time-to-event data, such as public health, engineering, biomedical science, actuarial science, and environmental science. This Special Issue will present a collection of the latest developments in survival models and their applications to new subject-matter challenges. Suitable topics include, but are not limited to, flexible but interpretable regression models, Bayesian survival models, spatial survival models, competing risk models, cure rate models, discrete survival models, methods for analyzing data in non-standard settings, and software development. Manuscripts that apply state-of-the-art survival models to new and ongoing real-world problems (e.g., the COVID-19 epidemic) are especially welcome. See this Special Issue website for manuscript submission information.