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
Irena 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
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 Gao, MBBS, MPH, MS
Statistical Genetics with interest in variance component analysis using summary statistics.
borang@umich.edu
Tian 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, 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 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 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 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 Roberts, B.A., MS
Survival analysis and causal inference including surrogate endpoints for clinical
trials.
ekrobe@umich.edu
Stephen 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 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
Lili 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
Wenbo 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 Yang, BS, MS
Estimation of the change points in the broken-stick model. Survival Analysis
yguangyu@umich.edu
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, 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 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, David Daiwei, BS, MS
Machine learning, statistical computing, statistical genetics, Bayesian methods
daiweiz@umich.edu
Xutong 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
Nina 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
