Courses are taught by SDS faculty and associated faculty members throughout the University.

The following faculty members served on the Graduate Studies Committee during the Spring 2015 semester:

adamsAdams, Paul
Department of Geography & the Environment
Research: Geography of communication technologies; representation of space and place

BeretvasBeretvas, Natasha S.
Department of Educational Psychology
Research: Application and evaluation of psychometric and statistical models, HLM, and meta-analytic techniques
Topics willing to supervise: multilevel (hierarchical) models, structural equation models, meta-analytic modeling techniques, psychometric models

Bickel 2Bickel, Eric J.  
Graduate Program in Operations Research
Research: Decision theory and its applications in the areas of energy, climate, economics, finance, and sports.
Topics willing to supervise: Entropy, strictly proper scoring rules, forecast verification, modeling of dependence, applications of decision theory

brocketBrockett, Patrick L.
Department of IROM
Research: Information systems, risk management, statistical analysis

carvalho2Carvalho, Carlos
SDS & Department of IROM
 Bayesian statistics in complex, high-dimensional problems with applications ranging from finance to genomics
CormackCormack, Lawrence
Department of Psychology
Research: Contrast processing in stereoscopic vision

Paul Damien
Research: Bayesian methods, knowledge management, option pricing, risk management
dhillonDhillon, Inderjit
Department of Computer Science
Research: Data mining, machine learning, numerical linear algebra, scientific computing, numerical optimization, bioinformatics

djurdjanovic draganDjurdjanovic, Dragan
Mechanical Engineering Department
Research: Maintenance decision-making in flexible and reconfigurable systems, applications of advanced signal processing in biomedical engineering

GreenbergGreenberg, Betsy S.
Department of IROM
Research: Statistical analysis

hasenbein johnHasenbein, John J.
Department of Mechanical Engineering
Research: Stochastic modeling, especially of complex manufacturing, computer, and telecommunication network systems
Topics willing to supervise: Queueing models and Markov decision processes (stochastic dynamic programming).

jessee1Jessee, Stephen
Department of Government
Research: American politics and statistical methodology, specifically political behavior using Bayesian statistics, ideal point estimation, and hierarchical models
Topics willing to supervise: Voting, public opinion, political behavior, ideology, judicial politics, legislative politics

KeittKeitt, Timothy H.
Section of Integrative Biology
Research: Importance of pattern and scale in landscapes in modifying ecological and evolutionary processes

KendrickKendrick, David
Department of Economics
Research: Control theory, stochastic modeling, computational economics, macroeconomics, and microeconomics

LinLin, Tse-Min
Department of Government
Research: Methodology, formal theory, & American and comparative political behavior

lueckeweb2Luecke, John E.
Department of Mathematics
Research: Topology and knot theory

LuskinRLuskin, Robert
Department of Government
Research: Political behavior, methodology, public opinion, voting behavior, and statistical methods

meyersLauren Meyers
SDS & Section of Integrative Biology
Mathematical epidemiology and theoretical evolutionary biology
morrice dMorrice, Douglas J.
Department of IROM
Research: Management science and supply chain management

MuellerMueller, Peter
SDS & Department of Mathematics
Research: Nonparametric Bayes, optimal design and decision problems, clinical trial design
Musick Marc 200607303Musick, Marc
Department of Sociology
Research: Medical sociology—social factors and health; religion and health; sociology of aging and the life course; and social psychology

PowersPowers, Daniel A.
Department of Sociology
Research: Substantive and methodological issues related to non-marital fertility and infant mortality.

pressPress, William
Department of Computer Science & Section of Integrative Biology
Research: Computational biology, genomics, and computational statistical methods

roberts brianRoberts, Brian
Department of Government
Research: American political institutions, interest groups, and positive political economy

saar TsechSaar-Tsechansky, Maytal
Department of IROM
Research: Data mining

sagerSager, Thomas W.
Department of IROM
Research: Statistical analysis
abhra 0051 1Sarkar, Abhra
Research: Developing sophisticated Bayesian non and semiparametric methods
Sarkar PSarkar, Purnamrita
large scale statistical machine learning problems with a focus on statistical models, asymptotic theory and scalable inference algorithms for large networks
Sarkar-CRSarkar, Sahotra
Section of Integrative Biology & Department of Philosophy
Research: Computational and mathematical biology, especially ecology and conservation biology

scottJames Scott
SDS & Department of IROM
Research: Bayesian model selection and multiple testing; connections between machine learning, compressed sensing, and Bayesian shrinkage estimation; variable selection and high-dimensional inference in non-linear, non-Gaussian models; and structured models for covariance matrices

shivelyShively, Thomas 
Department of IROM
Research: Time series regression models, nonparametric regression models, model selection, hierarchical Bayes models, marketing research and the statistical analysis of air pollution data
StolpeStolp, Chandler W.
LBJ School of Public Affairs
Research: Social policy evaluation, western hemispheric economic integration, and the application of innovative statistical methods in "messy" data environments

vonhippelVon Hippel, Paul
LBJ School of Public Affairs
Research: Statistics, demographic analysis, education policy, healthcare

walkerStephen G. Walker
SDS & Department of Mathematics
Research: Bayesian parametric and nonparametric methods with applications in medical statistics
wilkeWilke, Claus O.
Section of Integrative Biology
Research: Computational biology—using bioinformatical and statistical methods to analyze biological data sets, in particular whole-genome and high-throughput data sets
williamson SWilliamson, Sinead
SDS & Department of IROM
Research: Nonparametric Bayesian methods for machine learning, dependent nonparametric processes, nonparametric latent variable methods
zhouMingyuan Zhou
Department of IROM
 Bayesian statistics, machine learning; developing statistical theory and methods, hierarchical models, and efficient Bayesian inference for big data; nonparametric Bayesian modeling