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