Biostatistics 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


Marco Benedetti, BS, MS
Statistical methods for spatial and spatio-temporal data.
benedetm@umich.edu


Rupam Bhattacharyya, BS, MS
Regression Modelling, Bayesian Statistics, Statistical Genetics, Precision Medicine
rupamb@umich.edu


Jonathan 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
bossjona@umich.edu


chen irenaIrena Chen, B.A.
Bayesian methods for high dimensional/temporal data
irena@umich.edu


Zhongsheng Chen, BS, MS
Statistical methods for rare variant analysis
zhongshc@umich.edu


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.
ycchao@umich.edu


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.
ecchase@umich.edu


Theresa Devasia, BS, MS
Cancer Research, Survival Analysis and Clinical Trials
tdevasia@umich.edu


Diptavo Dutta, B.Sc., M.Stat. 
GWAS, Rare variants, pleiotropy, pathway-based association, variable selection
diptavo@umich.edu


Zhe Fei Zhe Fei 
High dimensional inference
feiz@umich.edu


Allison Furgal, BS, MS, M.A. 
Joint models for longitudinal and competing risks survival data, multivariate survival models, copula models
acullen@umich.edu


Cui Guo, BS, MS 
Bayesian methods and imaging statistics
cuiguo@umich.edu


Boran GaoBoran Gao, MBBS, MPH, MS
Statistical Genetics with interest in variance component analysis using summary statistics.
borang@umich.edu


Tian GuTian Gu, BS, MS
Health Data Science, Missing Data, Data Integration, Prediction Models
gutian@umich.edu


Sarah Hanks, B.A. 
Development and application of statistical methods for the analysis of human genetic and genomic data.
schanks@umich.edu


Wei Hao, BS, MS
Mediation Analysis
weihao@umich.edu


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.
ehector@umich.edu 


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.
abhukku@umich.edu


Kim HochstedlerKim Hochstedler, BS 
Clinical trials, survival analysis, cancer, mental illness
hochsted@umich.edu


Alan Kwong, BS, MS 
Statistical genetics, genetic association, next-generation sequencing
amkwong@umich.edu


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


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


Ying Ma, B.M., MS 
Statistical Genetics, Single cell data analysis
yingma@umich.edu


pedro orozcoPedro Orozco del Pino, BS, MS
Generalizability of Genetic Risk Scores
porozco@umich.edu


Robert Peng, B.A., MS
Use of polygenic risk scores to predict a patient's genetic risk for various diseases
rbpeng@umich.edu


Adam Peterson, BS, MS
Spatial-Temporal Aggregated Predictors: Methodology and accompanying software (rstap)and Classifying Built Environment Exposure
atpvyc@umich.edu


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


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


Lulu Shang, BS, MS
Genetics
shanglu@umich.edu


Yanyi Song, BS, MS
Bayesian method, mediation analysis, statistical genetics
yanys@umich.edu


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


Yilun Sun, BS, MS
Robust Methods in Missing Data and Dynamic Treatment Regimes
yilunsun@umich.edu


Ming Tang, BS, MS
Missing Data Analysis, Dynamic Treatment Regimes
mingtang@umich.edu


Nicole Wakim, BS, MS
Clinical trials, Alzheimer's research
nwakim@umich.edu


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


Wenjia Wang, BS, MS
Semiparametric and Joint Modeling of Survival in Cancer Screening Problems
icywang@umich.edu


Josh Weinstock, B.A., MS
WGS variant calling; Mendelian Randomization; clonal hematopoiesis
jweinstk@umich.edu


Whiteman, Andrew, BS, MS
Biostatistics; imaging statistics, computational methods
awhitem@umich.edu


wuWenbo Wu, B.A., M.A.
High-dimensional statistics, machine learning and optimization
wenbiwu@umich.edu


Jingyue Xi, BS, MS
Statistical Genetics and Single Cell Analysis
jyxi@umich.edu


Pranav Yajnik, BS, MS
Genetic Epidemiology, GWAS
pyajnik@umich.edu


guangyu yangGuangyu Yang, BS, MS
Estimation of the change points in the broken-stick model. Survival Analysis
yguangyu@umich.edu


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


Tsung-Hung Yao
Non-parametric Bayesian Statistics and Bayesian Network Methodology.
yaots@umich.edu


hengshi yu Hengshi Yu, BS, MS
Causal inference and statistical learning. Strong interest in the interplay between stochastic modeling and semi-parametric statistics.
hengshi@umich.edu


Ketian Yu, BS, M.S.
Statistical Genetics
yukt@umich.edu


Youfei Yu, B.A., MS
Causal inference approach for censored data and data with multiple treatments.
youfeiyu@umich.edu


Yuqi Zhai, BS, MS
Design and analysis of sample surveys, Bayesian inference and spatial statistics.
yqzhai@umich.edu


Gregory ZajacGregory JM Zajac, BS, MS.
Statistical methods and computational algorithms for the analysis of human genetic data. Current projects include genome-wide association studies, contamination, linkage, and meta-analysis.
gzajac@umich.edu

 


 

zhang daiweiZhang, David Daiwei, BS, MS
Machine learning, statistical computing, statistical genetics, Bayesian methods
daiweiz@umich.edu


zhao xutongXutong Zhao, BS, MS
Statistical genetics
xtzhao@umich.edu


Zhangchen Zhao, BS, M.S.
Gene-based tests and efficient resampling methods
zczhao@umich.edu


Yingchao Zhong, B.A., MS
Kidney transplantation registry data; survival analysis methods
zhongych@umich.edu


zhou ninaNina Zhou, BS, MS
Dynamic Treatment Regime, Missing Data and machine learning
zhounina@umich.edu


Jiaqiang Zhu, BS, MS
Statistical Genetics, Differential Gene Expression Analysis, Differential Methylation Analysis
jiaqiang@umich.edu


Yongwen Zhuang, BS, M.S.
Statistical methods in genetics, computational statistics, machine learning
zyongwen@umich.edu