Biostatistics PhD Student Profiles
This optional list does not include all of our PhD students.
Andy Beck, BS, MS
The use of population genetic data to understand the biological mechanisms underlying disease risk and heritability
Rupam Bhattacharyya, BS, MS
Regression Modelling, Bayesian Statistics, Statistical Genetics, Precision Medicine
Jonathan Boss, BS, MS
Continuous shrinkage priors, multi-pollutant modeling, high-dimensional mediation analysis, data integration. Applied collaborations in environmental statistics ranging from amyotrophic lateral sclerosis, birth outcomes, and racial differences in telomere length.
Irena Chen, B.A.
Bayesian methods for high dimensional/temporal data
Statistical methods for sequential multiple assignment randomized trial (SMART) in small samples. In particular,developing methods to estimate the response rates of treatments or dynamic treatment regimes in SMART when the outcome of interest is binary. Application of adaptive designs in SMART
Elizabeth Chase, BSP.H., MS
Bayesian shrinkage methods for semiparametric modeling. Applied collaborations in prostate cancer and the Flint water crisis
Theresa Devasia, BS, MS
Cancer Research, Survival Analysis and Clinical Trials
Allison Furgal, BS, MS, M.A.
Joint models for longitudinal and competing risks survival data, multivariate survival models, copula models
Boran Gao, MBBS, MPH, MS
Statistical Genetics with interest in variance component analysis using summary statistics
Tian Gu, BS, MS
Health Data Science, Missing Data, Data Integration, Prediction Models
Sarah Hanks, B.A.
Development and application of statistical methods for the analysis of human genetic and genomic data.
Wei Hao, BS, MS
Holly Hartman, BS, MS
Clinical trial design, survival analysis, predictive risk modeling, health inequities, applications in oncology
Nicholas Hartman, BS
Survival Analysis, Population Health Data
Mengtong Hu, BS
Precision Medicine, Health Data Science, Causal Inference
Abhay Hukku, BS, MS
Development of statistical methodology to address problems in human genetics. Currently working on new methods for conducting gene-set based analyses
Kim Hochstedler, BS, MS
Clinical trials, survival analysis, cancer, mental illness
Zheng Li, MS
Statistical genetics, spatial transcriptomics analysis, mWAS
Ying Ma, B.M., MS
Statistical Genetics, Single cell data analysis
Analysis of RNA-seq and ATAC-seq data from the Finland United States Investigation of NIDDM Genetics (FUSION) study
Pedro Orozco del Pino, BS, MS
Generalizability of Genetic Risk Scores
Adam Peterson, BS, MS
Spatial-Temporal Aggregated Predictors: Methodology and accompanying software (rstap)and Classifying Built Environment Exposure
Nathaniel Putnam, BS, MS
Mobile health, spatial statistics, survival analysis
Emily Roberts, B.A., MS
Causal inference including surrogate endpoint validation for clinical trials and applications in oncology
Stephen Salerno, BS, MS
Statistical methodology and its applications to clinical quality measure development, health policy, and global public health.
Fatema Shafie Khorassani, BS, MPH, MS
Causal inference, data integration, electronic health records, and missing data. Survival and longitudinal data methods in applications related to stroke, health disparities, tobacco use, and cancer.
Lulu Shang, BS, MS
Causal Inference, Dynamic Treatment Regime
Nicole Wakim, BS, MS
Clinical trials, Alzheimer's research
Wenjia Wang, BS, MS
Semiparametric and Joint Modeling of Survival in Cancer Screening Problems
Josh Weinstock, B.A., MS
WGS variant calling; Mendelian Randomization; clonal hematopoiesis
Andrew Whiteman, BS, MS
Biostatistics; imaging statistics, computational methods
Jung Yeon Won, BBS, MS
Measurement error models, Data integration, Latent variable model, Built-environment data
Wenbo Wu, B.A., M.A.
High-dimensional statistics, machine learning and optimization
Jingyue Xi, BS, MS
Statistical Genetics and Single Cell Analysis
Pranav Yajnik, BS, MS
Genetic Epidemiology, GWAS
Guangyu Yang, BS, MS
Semiparametric Model; Change-Point Detection
Non-parametric Bayesian Statistics and Bayesian Network Methodology.
Hengshi Yu, BS, MS
Causal inference and statistical learning. Strong interest in the interplay between stochastic modeling and semi-parametric statistics
Ketian Yu, BS, M.S.
Youfei Yu, B.A., MS
Causal inference approach for censored data and data with multiple treatments.
Yuqi Zhai, BS, MS
Design and analysis of sample surveys, Bayesian inference and spatial statistics.
David Daiwei Zhang, BS, MS
Machine learning, statistical computing, statistical genetics, Bayesian methods
Yuhua Zhang, MS
Zhangchen Zhao, BS, M.S.
Gene-based tests and efficient resampling methods
Yingchao Zhong, B.A., MS
Kidney transplantation registry data; survival analysis methods
Nina Zhou, BS, MS
Dynamic Treatment Regime, Missing Data and machine learning
Jiaqiang Zhu, BS, MS
Statistical Genetics, Differential Gene Expression Analysis, Differential Methylation Analysis
Yongwen Zhuang, BS, M.S.
Statistical methods in genetics, computational statistics, machine learning