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Statistics Research Areas

There are currently nine full-time faculty members in the Department of Statistics. The goal of our Ph.D. program is to train statistical researchers to be leaders in the development of statistical methodology and statistical theory, and to be active participants in interdisciplinary collaborations.

Below is a partial list of research areas in which our faculty participate.

  • Astrostatistics
  • Bayesian Statistics
  • Biostatistics
  • Genomics
  • Statistical Computing
  • Statistics Education
  • Time Series

DANIEL GILLEN, Professor and Chair (Ph.D, University of Washington) – Research interests: Biostatistics, survival analysis methodology for modeling censored time to event data, group sequential testing, and the design and analysis of clinical trials. Primary area of interdisciplinary work is in clinical research with an emphasis in renal disease and cancer.

MICHELE GUINDANI, Associate Professor (Ph.D., Università Bocconi) – Research interests: Analysis of high-dimensional data, including genomic and imaging data; data integration for combining information from several data platforms, and relating them with measurable outcomes (integrative genomics, imaging genomics); statistical decision-making under uncertainty; multiple comparison problems; clustering; Bayesian modeling; Bayesian Nonparametrics.

WESLEY JOHNSON, Professor Emeritus (Ph.D., University of Minnesota) – Research interests: Bayesian parametric, nonparametric and semiparametric methods and inference for survival analysis, longitudinal and spatial data and for diagnostic outcome data and protocols. Asymptotics for Bayesian inference. Development of informative and partially informative prior distributions. Primary area of interdisciplinary work is veterinary and human epidemiology.

VLADIMIR MININ, Professor (Ph.D., UCLA) – Research interests: Biological sciences; infectious disease epidemiology, working on Bayesian estimation of disease transmission model parameters; computational immunology, working on statistical methods to analyze high throughput sequence data of B-cell receptors; and phylogenetics, population genetics and systems biology.

BIN NAN, Professor (Ph.D., University of Washington) – Research interests: Various areas of statistics and biostatistics, including semiparametric inference, failure time and survival analysis, longitudinal data, missing data and two-phase sampling designs, and high-dimensional data analysis.

HERNANDO OMBAO, Professor (Ph.D., University of Michigan) – Research interests: Spatio-temporal models, time series theory and methods, signal and image processing, functional data analysis, collaborative research in neuroscience, psychiatry, cardiology, cognitive science and finance.

BABAK SHAHBABA, Associate Professor (Ph.D., University of Toronto) – Research interests: Bayesian inference, Bayesian nonparametric modeling, biostatistics, computational methods, Markov chain Monte Carlo algorithms, applied statistics.

WEINING SHEN, Assistant Professor (Ph.D., North Carolina State University) – Research interests: Bayesian nonparametric/semi-parametric models, asymptotics, high-dimensional inference and variable selection, biomarker evaluation, risk prediction of cancer, Bayesian clinical trial designs, longitudinal data analysis.

HAL STERN, Professor (Ph.D., Stanford) – Research interests: Statistical inference using Bayesian methods and model diagnostics. Primary area of interdisciplinary work is applications in the biological and social sciences.

JESSICA UTTS, Professor (Ph.D., Pennsylvania State University) – Research interests: Statistics education; Interdisciplinary statistical applications, most notably in the use of statistics in parapsychology.

YAMING YU, Associate Professor (Ph.D, Harvard University) – Research interests: Statistical computing, Bayesian analysis, applied probability, applications of statistics to astronomy.

ZHAOXIA YU, Associate Professor (Ph.D, Rice University) – Research interests: Genome-wide association analysis, haplotype-based analysis, gene-gene and gene-environment interactions, gene regulatory network, genetic pathway.