Biostatistics PhD Student Profiles

This is not a complete list of our PhD students (listing optional)

Andy Beck, BS, MS
Fine mapping of mutation rates across the genome
beckandy@umich.edu


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


Jonathan Boss, BS, MSJonathan Boss, BS, MS 
Multi-pollutant modeling, non-linear interaction selection in the presence of many environmental contaminants, and statistical inference when exposure data are subject to multiple detection limits. Applied collaborations in environmental statistics ranging from amyotrophic lateral sclerosis, racial disparities in telomere length, and gestational duration in pregnant women


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


Zhongsheng Chen, BS, MS
Statistical methods for rare variant analysis


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 Chase, BSP.H., MS
Research interests still developing. Thus far, working on penalized regression and epidemiologic methods, with applications in cancer, HIV, women's health, and health disparities. Other interests include causal inference, missing data, neighborhood/network effects, and electronic health records.


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.


Emily Hector Emily Hector, BS, MS
 Estimating equations, Composite likelihood, Generalized method of moments, Divide- and-conquer, Heterogeneous data integration, High-Dimensional data, Correlated data, Parallel computing.


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


Pin Li, BS, MS
Clinical trials, predictive risk modeling, use of biomarkers to individualize and adapt treatment.


lan luoLan Luo, BS, MS
Streaming Data Analytics and Real-time Regression Analysis.


Ying Ma, B.M., MS 
Statistical Genetics, Single cell data analysis


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


Emily RobertsEmily Roberts, B.A., MS 
Survival analysis and causal inference including surrogate endpoints for clinical trials.


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


Lulu Shang, BS, MS
Genetics


Yanyi Song, BS, MS
Bayesian method, mediation analysis, statistical genetics


Kelly SpethKelly Speth, BS, MS 
Dynamic treatment regimes, observational data, machine learning, cancer biostatistics.


Ming Tang, BS, MS
Missing Data Analysis, Dynamic Treatment Regimes


Nicole Wakim, BS, MS
Clinical trials, Alzheimer's research


wang liliLili Wang, BS, M.S.
Survival analysis, recurrent events, mixed-effects models, and causal inference.


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


Whiteman, Andrew, BS, MS
Biostatistics; imaging statistics, computational methods


wuWenbo 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 yangGuangyu Yang, BS, MS
Estimation of the change points in the broken-stick model. Survival Analysis


yuan yang Yuan Yang, BS, M.S.
Nonparametric regression, high dimensional data, statistical inference, variable selection, and survival analysis.


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 daiweiZhang, David Daiwei, BS, MS
Machine learning, statistical computing, statistical genetics, Bayesian methods


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