Biostatistics PhD Student Profiles

This optional list does not include all of our PhD students.

Andy BeckAndy Beck, BS, MS
The use of population genetic data to understand the biological mechanisms underlying disease risk and heritability

rupam bhattacharyyaRupam Bhattacharyya, BS, MS
Regression Modelling, Bayesian Statistics, Statistical Genetics, Precision Medicine

Jonathan Boss, BS, MSJonathan 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.

chen irenaIrena Chen, B.A.
Bayesian methods for high dimensional/temporal data

Yan-Cheng Chao 
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 ChaseElizabeth 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 GaoBoran Gao, MBBS, MPH, MS
Statistical Genetics with interest in variance component analysis using summary statistics

Tian GuTian 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
Mediation Analysis

Holly HartmanHolly 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 HuMengtong 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 HochstedlerKim 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

Jeff Okamoto
Analysis of RNA-seq and ATAC-seq data from the Finland United States Investigation of NIDDM Genetics (FUSION) study

pedro orozcoPedro 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 RobertsEmily Roberts, B.A., MS 
Causal inference including surrogate endpoint validation for clinical trials and applications in oncology

Stephen SalernoStephen Salerno, BS, MS 
Statistical methodology and its applications to clinical quality measure development, health policy, and global public health.

Fatema Shafie KhorassaniFatema 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
Genetics

Ming TangMing Tang
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

wuWenbo Wu, B.A., M.A.
High-dimensional statistics, machine learning and optimization

Jingyue Xi, BS, MS
Statistical Genetics and Single Cell Analysis

Yuliang XuYuliang Xu

Pranav Yajnik, BS, MS
Genetic Epidemiology, GWAS

guangyu yangGuangyu Yang, BS, MS
Semiparametric Model; Change-Point Detection

Tsung-Hung Yao
Non-parametric Bayesian Statistics and Bayesian Network Methodology.

hengshi yu 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.
Statistical Genetics

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.


zhang daiweiDavid Daiwei Zhang, BS, MS
Machine learning, statistical computing, statistical genetics, Bayesian methods

Yuhua Zhang, MS
Network Modeling

Zhangchen Zhao, BS, M.S.
Gene-based tests and efficient resampling methods

Yingchao Zhong, B.A., MS
Kidney transplantation registry data; survival analysis methods

zhou ninaNina 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