Biostatistics Faculty Profiles

Department of Biostatistics faculty and researchers have achieved national and international reputations for excellence in their field. Read more about our faculty below, and click on a name to view the full faculty profile.

Department Chair

Bhramar Mukherjee, PhD
Statistical Methods in Epidemiology; Analysis of Electronic Health Records and Biobank Data; Shrinkage and Selection Problems; Gene-Environment Interaction; Bayesian Modeling and Inference; Cancer, Reproductive, Cardiovascular Epidemiology and Environmental Health.

Core Faculty

Goncalo Abecasis, DPhil
Identification of genes involved in complex disease, with a special emphasis on developing analytical methods that help geneticists reap the full benefits of new high-throughput technologies.

Veera Baladandayuthapani, PhD 
Methodology: Bayes; big data, health data science, functional data, graphical models, integrative modeling, machine learning, nonlinear/nonparametric models, spatial data, statistical computing. Application areas: Cancer, high-throughput genomics, epigenomics, transcriptomics and proteomics, high-resolution neuro- and cancer- imaging, clinical trials, precision medicine

Mousumi Banerjee, PhD
Machine learning in healthcare, methods for analyzing observational data, prognostic modeling, correlated data, survival analyses, competing risks, health services and outcomes research

Michael Boehnke, PhD
Understanding the genetic basis of human health and disease, design and analysis of human gene mapping studies, genome-wide association studies based on array genotyping and whole genome sequencing, and genetics of type 2 diabetes and related traits.

Philip S. Boonstra, PhD
Shrinkage estimators, hierarchical models, high-dimensional data analysis, measurement error problems, cancer epidemiology, cancer genetics/genomics, and early-phase oncology clinical trials.

  F. DuBois Bowman, PhD
Parkinson's disease, Alzheimer's disease, depression, schizophrenia, and substance addiction.

Thomas Braun, PhD
Health disparities in cancer immunotherapy use; treatment discovery for rare diseases; Bayesian adaptive clinical trial design; power prior models for combining datasets; hierarchical & longitudinal data methods; permutation and resampling methods

Walter Dempsey, PhD
Statistical Methodology: survival and longitudinal analysis; statistical network analysis; causal inference and sequential decision making; experimental design; statistical models for exchangeable stochastic processes; functional data analysis. Application areas: mobile health, digital health , biomedical data 

Michael R. Elliott, PhD
Design and analysis of sample surveys, causal modeling inference, and latent variable models for longitudinal data with applications to injury epidemiology, reproductive epidemiology, and social determinants of health.

 Lars Fritsche, PhD
Analyses that combine genetic information obtained from sequencing and genotyping arrays with extensive phenotypic data collected using electronic health records and other population scale approaches.

Peisong Han, PhD
Missing data problems in public health studies and survey sampling, and data integration

Wei Hao, PhD

Zhi (Kevin) He, PhD
Survival analysis, high-dimensional data analysis, statistical genetics, statistical methods for epidemiology and causal inference, and statistical methods for analyzing large-scale data arising from CKD and ESRD studies.

Nicholas Henderson, PhD
Precision medicine, Empirical Bayes methods, Bayesian nonparametrics, Bayesian machine learning methods, Computational statistics, Survival analysis, Data integration

Hui Jiang, PhD
Bioinformatics, statistical genomics and computational statistics.

Timothy D. Johnson, PhD
Statistical modeling of biomedical data. Bayesian and MCMC methodology with and emphasis on mixture models and variable parameter spaces. Applications in neurology, cancer, radiology and endocrinology.

Jian Kang, PhD
Statistical Methods for Big data, Bayesian methods, Imaging Statistics (fMRI, PET and DTI), Spatial Statistics, Independent Component Analysis, Composite Likelihood, Graphical Models, Survival Analysis, Longitudinal data analysis, Functional data analysis, Bioinformatics and Statistical Genetics.

Hyun Min Kang, PhD
Genome-wide association mapping with next-generation sequencing data, population stratification in association studies, genetics-driven approach to drug discovery. Statistical and computational method development in genetics.

Kelley M. Kidwell, PhD
Survival analysis, adaptive treatment strategies, and applications to cancer research.

Gen Li, PhD
Microbiome data analysis; tensor array methods; low-rank models; multi-view data integration; high-dimensional data analysis.

 Yi Li, PhD
High-dimensional data analysis with applications in genetics/genomics, survival analysis, longitudinal and correlated data analysis, measurement error problems, spatial models and clinical trial design.

Roderick J.A. Little, PhD
Statistical analysis with missing data, inference from complex surveys, Bayesian methods, applications of statistics in epidemiology, neurology, cancer, social sciences.

Jean Morrison, PhD
Genetic associations with high dimensional phenotypes, mendelian randomization.

Bhramar Mukherjee, PhD
Statistical Methods in Epidemiology; Analysis of Electronic Health Records and Biobank Data; Shrinkage and Selection Problems; Gene-Environment Interaction; Bayesian Modeling and Inference; Cancer, Reproductive, Cardiovascular Epidemiology and Environmental Health.

Susan Murray, ScD
Survival analysis, missing data issues, quality of life research, group sequential monitoring of survival endpoints, correlated survival endpoints, pulmonary research.

Trivellore Eachambadi Raghunathan, PhD
Statistical analysis of incomplete data, multiple imputation, Bayesian inference, design and analysis of sample surveys, small area estimation, analysis of longitudinal data, confidentiality and disclosure limitation, cardiovascular epidemiology.

Laura Scott, PhD
Integration of mRNA, miRNA, methylation and regulatory element (ATAC-Seq data) data with genetic and phenotypic information, single cell genomics, use of biological data to evaluate and identify disease-causing variants, methods development for experimental data analysis, identification of genetic variants that increase risk of type II diabetes and bipolar disorder/schizophrenia in multiple ancestries, complex diseases study design, evaluation of imputation quality across ancestries.

Xu Shi, PhD
Electronic health records, causal inference, data corruption, record linkage, machine translation, semiparametric efficiency theory, postmarketing safety surveillance, healthcare policy.

Peter X.K. Song, PhD
Longitudinal data analysis, missing data problems in clinical trials, statistical methods in bioinformatics and genetics, and time series analysis.

Cathie Spino, Sc.D.
Clinical trials methodology, particularly adaptive designs, and women's and children's health.

Jeremy M G Taylor, PhD
Longitudinal and survival analysis, cure models, missing data, Box-Cox transformations, statistical methods for bioinformatics, surrogate and auxiliary variables, statistical modelling of biomedical data.

Alexander Tsodikov, PhD
Multivariate semiparametric survival models, applications in cancer.

Lu Wang, PhD
Statistical methods for evaluating dynamic treatment regimes, personalized health care, nonparametric and semiparametric regressions, missing data analysis, and longitudinal (correlated/clustered) data analysis, epidemiology, observational studies, clinical trials.

Xiaoquan William Wen , PhD
Bayesian and Computational Statistics with applications in genetics and genomics.

Zhenke Wu, PhD
Bayesian Hierarchical Latent Variable Models, Robust Inference for Experimental and Observational Data, Open-Source Software Platform for Learning Health Communities

Wen Ye, PhD
Clinical trials and epidemiological studies, particularly measurement error, informative dropout, missing data, and non-compliance issues

Sebastian Zöllner, PhD
Population genetics, copy number variation, rare variants, genetics of psychiatric diseases

 Matthew Zawistowski, PhD
Statistical and Population Genetics, Electronic Health Records, Risk Prediction, Precision Medicine, Statistics Education

Min Zhang, PhD
Semiparametric methods with missing and censored data, causal inference,survival analysis, clinical trials, and longitudinal data analysis

Lili Zhao, PhD
Bayesian Modeling and Inference, Survival Analysis, Analysis of Electronic Health Records Data, Clinical Trials, Analysis for Large Contingency Table, Deep Neural Network, Cancer, Vaccine Safety, Immunotherapy Safety

Xiang Zhou, PhD
Computational and Statistical Methods for Large-Scale Genetic and Genomic Studies

Faculty with Joint Appointments

Andrzej T. Galecki, M.D., PhD
Developing computational methods for analyzing correlated and over dispersed data.

Lana Garmire, PhD
Single-cell sequencing and bioinformatics. Integrative omics/clinic data analysis. Translational bioinformatics of cancers and immune-related diseases, such as classifying biomarkers for cancer prognosis and diagnosis. Pregnancy adversities and fetal orgin of cancers, public health genomics.

Brenda Gillespie, PhD
Applied biostatistics, particularly survival analysis, clinical trials, and applications of biostatistics to epidemiology.

Niko Kaciroti, PhD
Longitudinal data analysis, Bayesian methods, missing-data, clinical trials. Application of statistics in an interdisciplinary setting: medical and social science, developmental data, managing chronic disease, global health.

Rahul Ladhania, PhD
Causal inference and machine learning in public and behavioral health

Stephen CJ Parker, PhD
Diabetes genetics, statistical genetics, chromatin, epigenomics, transcriptomics

Arvind Rao, PhD
Transcriptional Genomics, Image Informatics, Heterogeneous Data Integration, Informatics for Combinatorial Drug Screens

Maureen A. Sartor, PhD
Developing statistical methodology for high throughput genomic and epigenomic experiments and other bioinformatic applications.

Matthew J. Schipper, PhD
Early phase oncology trial design, predictive risk modeling and use of biomarkers to individualize and adapt treatment.

Ananda Sen, PhD
Analysis of recurrent event data in both biomedical and engineering contexts. Competing risks, and accelerated failure time modeling.

Kerby Shedden, PhD
Statistical modeling in the natural sciences. High dimensional and massive data sets. Statistical computing.

Yajuan Si, PhD
Bayesian statistics, multilevel regression and poststratification, latent variable models, high-dimensional data, categorical data analysis, missing data imputation, complex survey inference, weighting approaches, causal inference and data confidentiality protection, with applications on epidemiogoly and health services research.

Lecturers and Adjunct Faculty

Veronica Berrocal, PhD
Development and application of statistical methods for data that exhibit some form of dependence, in particular spatial/spatio-temporal data, and longitudinal data.

Hyungjin Myra Kim, ScD
Evaluation of feasibility, effectiveness, and accuracy of various telemedicine approaches compared with traditional onsite medical care; medical decision analysis; cost-effectiveness analysis.

Shawn Lee, PhD
Developing statistical and computational methods for the analysis of the large-scale high-dimensional genomic data.

Bin Nan, PhD
Semiparametric regression models, survival analysis, high-dimensional data analysis, cohort studies, clinical trials.

Brisa Sanchez, PhD
Statistical methodology applicable to environmental epidemiology, and social epidemiology, and health disparities.

Douglas E. Schaubel, PhD
Causal inference; temporal process regression; survival analysis; health services research; recurrent/terminal events.

Emeritus Faculty

Morton B. Brown, PhD
Clinical trials, categorical data analysis, statistical computing, robust methods and model fitting.

Jack D. Kalbfleisch, PhD
Development of statistical methods and theory, survival and event history analysis, design and analysis of clinical trials, mixture models, stochastic modeling, applications in renal disease and organ transplantation.

James M. Lepkowski, PhD
Survey methodology, particularly sampling design and estimation, telephone sample design, handling unit and item nonresponse, variance estimation, analysis of complex sample survey data, and respondent-interviewer interaction in the survey process.