Statistics Department faculty and their research interests are listed below. Links to individual faculty pages are available by referring to the Faculty Directory.

**Cecile Ané, Professor:** Statistical inference for evolutionary biology, computational biology

**Richard Chappell, Professor:** Biostatistics, epidemiology, missing data, allometry

**Peter Chien, Professor:** Big data analytics, uncertainty quantification, A/B testing, design of experiments

**Jessi Cisewski-Kehe Assistant Professor:**Astrostatistics, cosmostatistics, exostatistics, topological data analysis, persistent homology, approximate Bayesian computation, visualization, data science, interdisciplinary research

**Nicolas Gracia Trillos, Assistant Professor:** Applied analysis, applied probability, computational probability and statistics, machine learning

**Hyunseung Kang, Assistant Professor:** Causal inference, instrumental variables, and econometrics, developing methods for causal inference using large observational data with applications to epidemiology, genetics, social policy evaluation, and online data

**Sunduz Keles, Professor:** Biostatistics, statistical genomics & computational biology, censored data analysis

**Bret Larget, Professor:** Statistical applications in the biological sciences, Bayesian statistics, computational biology, phylogenetics.

**Keith Levin, Assistant Professor: **Network analysis, covariance estimation, bootstrap methods, randomized linear algebra, high-dimensional statistics

**Po-Ling Loh, Associate Professor:** High-dimensional statistics, compressed sensing, nonconvex optimization, robust statistics, network inference

**Wei-Yin Loh, Professor:** Statistical inference; bootstrap theory and methods; decision tree algorithms for data mining and prediction with applications to missing value imputation, sample surveys, causal inference, and subgroup identification for precision medicine

**Michael Newton, Professor:** Stochastic modeling, computational biology, empirical Bayesian analysis, ranking, biomedical applications

**Vivak Patel, Assistant Professor:** Incremental Estimation and Asymptotic Statistics; Numerical Optimization Theory and Algorithms; Statistical Filtering; Applications to Dynamical Systems.

**Sebastian Raschka, Assistant Professor:** Deep learning with a focus on privacy protection and protection against adversarial attacks, automatic machine learning (AutoML), machine learning model evaluation, and machine learning applied to molecular modeling.

**Garvesh Raskutti, Associate Professor:** Optimization theory, information theory and theoretical statistics to study computational and statistical aspects of large-scale inference problems

**Karl Rohe, Associate Professor:** Regression and network clustering, machine learning, knowledge creation with statistics

**Jun Shao, Professor:** Inference, asymptotic theory, resampling methods, linear and nonlinear models, model selection, sample survey

**Miaoyan Wang, Assistant Professor:** Statistical machine learning, higher-order tensors, numerical multi-linear algebra, statistical/population genetics.

**Yazhen Wang, Professor:** Financial statistics & financial data science, quantum computing, quantum tomography, high-dimensional statistical inference, machine learning, wavelets, nonparametric smoothing, change points, long-memory process, and order restricted statistical inferences

**Brian Yandell, Professor:** Nonparametrics, biometry, gene mapping, generalized linear models

**Anru Zhang, Assistant Professor:** High-dimensional statistical inference, statistical learning theory, tensor data analysis, compressed sensing and matrix recovery, applications in genomics

**Chunming Zhang, Professor:** Neuroinformatics and bioinformatics, machine learning and data mining, multiple testing, large-scale simultaneous inference and application, statistical methods in finance econometrics, non- and semi-parametric estimation and inference, functional and longitudinal data analysis

**Zhengjun (Henry) Zhang, Professor:** Extreme value analytics for big data and financial time series analysis; risk analysis in finance, insurance, environmental studies, and seismic data; nonlinear/asymmetric causal inference; hi-dimensional inference; medical statistics; stochastic optimization and simulation technique; Bayesian inference for time series

**Jun Zhu, Professor:** Spatial statistics, spatio-temporal statistics, Markov random fields, agricultural statistics, environmental statistics, statistical ecology, environmental/population health, disease mapping, medical imaging, spatial demography

**Affiliated Faculty**

**David Anderson, Professor:** Developing and analyzing new computational methods for the stochastic models that arise in the biosciences; theoretical study of the mathematical models arising in the biosciences

**Karl Broman, Professor:** Statistical genomics, computational biology, statistical computing, data visualization, general applied statistics

**Guanhua Chen, Assistant Professor:** causal inference, semiparametric inference, statistical/machine learning and -omics data

**Moo Chung, Associate Professor:** Brain Image Analysis, Brain Network Analysis, Topological Data Analysis, Functional Data Analysis, Shape Analysis

**Christina Kendziorski Newton, Professor:** Statistical genetics and computational biology, Bayes and empirical Bayes methods

**Ronald Gangnon, Professor:** Spatial statistics, Bayes and empirical Bayes methods, ranking, age-period-cohort models, measurement error, epidemiology

**Kyung Mann Kim, Professor:** Sequential methods, clustered data analysis, categorical data analysis, biostatistics, clinical trials methods, epidemiology methods

**Qiongshi Lu, Assistant Professor:** Statistical genetics, genetic risk prediction, genome-wide association study, genome annotation, genomic data integration

**Lu Mao, Assistant Professor:** Survival analysis, semiparametric inference, design and analysis of clinical trials, nonparametric estimation under shape constraint

**Robert Nowak, Professor:** Machine learning and high-dimensional statistics

**Mari Palta, Professor:** Biostatistical methods and epidemiology

**Timo Seppalainen, Professor:** Probability theory, random environments and random potentials, interacting particle systems, and large deviation theory

**Zhengzheng Tang, Assistant Professor:** Statistical Genetics, Genetics Association Analysis, Meta-analysis, Microbiome & Metagenomic Data, Multi-Omics Data.

**Menggang Yu, Professor:** Clinical Biostatistics and Personalized Medicine, Causal Inference, Risk Prediction, Survival Analysis

**Claudia Solis-Lemus**, Assistant Professor: Statistical phylogenomics and genomics, computational biology, machine learning, high-dimensional statistics, microbiome network analysis

## Emeriti

**Douglas Bates, Professor Emeritus:** Nonlinear regression, statistical computing

**Murray Clayton, Professor Emeritus:** Applications of statistics to the agricultural, biological, and environmental sciences; spatial statistics, foundations

**Norman Draper, Professor Emeritus:** Experimental design, linear models, nonlinear estimation

**Erik Nordheim, Professor Emeritus:** Biological statistics, design and analysis, applied linear models

**Richard Johnson, Professor Emeritus:** Life testing & reliability, statistical inference, large sample theory, applied multivariate analysis

**Robert Wardrop, Professor Emeritus:** Online statistical education, statistics in sports

**Kjell Doksum, Senior Research Scientist:** Nonparametric regression, biostatistics

**Kam-Wah Tsui, Professor Emeritus:** Decision theory, survey sampling, statistical inference

**Grace Wahba, Professor Emerita:** Statistical machine learning, including complex models with heterogenous interacting inputs and outputs. Applications in Biostatistics and Physical Sciences.