Statistics & Data Science GIDP Faculty

Click on photo for additional information on a faculty member.

Lingling An

Member of Executive Committee
Associate Professor, Biosystems Engineering
Statistical genomics/metagenomics; Single cell data analysis; Data mining and machine learning

Kobus Barnard

Professor, School of Mind, Brain and Behavior
Machine learning; Mathematical modeling of geometric form; Multi-modal data; Statistical applications in computer vision.

Andrew Bennett

Assistant Professor, Hydrology and Atmospheric Sciences
Research interests include computational hydrology, with a focus on deep learning, physically based models and hybrid differentiable models. Also scientific computing and open science.
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Alexander Bucksch

Associate Professor - School of Plant Sciences
​​Our​ research is motivated by the threads that climate change imposes on the agricultural and natural plant ecosystem. Therefore, we develop imaging and simulation approaches to understand the function of natural variation in plants

Melinda Davis

Research Assistant Professor
Latent variable modeling; Measurement of change; Item response theory; Health outcomes research; Statistical consulting.

Hongxu Ding

Assistant Professor, Translational Pharmacogenomics
Single-cell analysis, nanopore sequencing. His lab develops computational biology approaches to interpret single-cell omics profiles and nanopore sequencing readouts.

Neng Fan

Associate Professor, Systems and Industrial Engineering
Methodologies in Optimization; Applied Operations Research; Data Mining and Machine Learning

Ryan Gutenkunst

Professor, Molecular and Cellular Biology
Computational biology, with focus on inferring history and natural selection from population genomic data

Ning Hao

Member of Executive Committee
Associate Professor, Mathematics
High dimensional data; Machine learning; Change point detection

Afrooz Jalilzadeh

Assistant Professor of Systems and Industrial Engineering
Research is focused on the design, analysis, and implementation of stochastic approximation methods for solving convex optimization and stochastic variational inequality problems with applications in machine learning, game theory, and power systems.

Nicole Kersting

Associate Professor, College of Education
Measurement and educational assessment; Item response and generalizability theory; Value-added models; Random effects models.

Haiquan Li

Assistant Professor Medicine
Biomedical big data science, Translational bioinformatics, bioinformatics, clinical informatics.

Jingjing Liang

Assistant Research Professor, R Ken Coit College of Pharmacy
Statistical genetics and genomics, including computational methods for analyzing large-scale sequencing data, rare variant association analysis, genomics-driven drug target discovery and precision medicine

Mingyu Liang

Professor and Department Head, Physiology
The Liang group studies molecular systems medicine. e. The current work in our group focuses on three areas: (epi)genomics and precision medicine, regulatory RNA, and cellular metabolism, as they relate to hypertension, cardiovascular and kidney disease.

Kevin Lin

Associate Professor Mathematics
Stochastic nonlinear phenomena in biology and physics, especially problems from computational neuroscience and nonequilibrium statistical physics; Monte Carlo algorithms; numerical methods for stochastic differential equations; scientific computing.

Lifeng Lin

Associate Professor, Epidemiology and Biostatistics
Dr. Lin has worked extensively on statistical methods for meta-analysis, network meta-analysis of multiple-treatment comparisons, publication bias, and Bayesian methods. He is also interested in the applications of statistical methods to real-world proble

Jian Liu

Associate Professor, Systems & Industrial Engineering
Dr Liu's research is in the integration of manufacturing engineering knowledge, control theory and advanced statistics for product quality and productivity improvement. His recent research focuses on system prognostic/diagnostic modeling and analysis and

Yiwen Liu

Assistant professor of Epidemiology and Biostatistics
Dimension reduction and variable selection, big data analytics, data integration

Clayton Morrison

Professor, School of Information
Machine Learning, Causal Inference, Activity Recognition and Understanding, Automated Planning, Knowledge Representation, Computational Cognitive Science

Jason Pacheco

Assistant Professor, Computer Science
Statistical machine learning, probabilistic graphical models, approximate inference algorithms, and information-theoretic decision making

Liliana Salvador

Assistant Professor, Animal & Comparative Biomedical Sciences
Multidisciplinary approach to study the dynamics of zoonotic infectious diseases. We develop computational, mathematical and data-driven models to understand the ecology and evolution of infectious diseases at the wildlife, livestock and human interface.

Bruce Walsh

Professor, Ecology and Evolutionary Biology
Biostatistics; Statistical genetics/genomics; Mixed models; Bayesian analysis; Resampling and MCMC methods.

Erfan Yazdandost Hamedani

Assistant Professor, Systems and Industrial Engineering
Methodologies in Optimization: Saddle point problems, Distributed Optimization, Bilevel Optimization.Applications: Machine Learning, Data Science, Artificial Intelligence

Affiliate Members 

Affiliate Members of the GIDP in Statistics are those with a general interest in statistical issues who wish to be fully informed of the Program’s operation, and who wish to engage in a limited subset of Program activities. Affiliate members often rotate to Regular status at pertinent intervals, and vice versa.

  • Ronald L. Breiger, Ph.D. Professor of Sociology. Statistical models for social network analysis; Log-linear models; Log-multiplicative models for contingency tables.
  • Emily A. Butler, Ph.D. Assistant Professor of Family and Consumer Sciences. Multivariate time-series analysis; Multilevel modeling; Dyadic models; Social-relations modeling.
  • Robert Canales, Ph.D. Assistant Professor of Public Health (Stanford University) Data mining, machine learning, analysis of complex systems; Application of Monte Carlo simulation and stochastic processes in risk analysis and environmental exposure assessment; Sensitivity analysis; Uncertainty and variability quantification
  • Andrew C. Comrie, Ph.D. Professor of Geography & Regional Development; Senior Vice President for Academic Affairs and Provost. Statistics of climate data; Data reduction; Spatial modeling.
  • Gautam Gowrisankaran, Ph.D. Professor of Economics. Structural econometric modeling; Applied Bayesian econometrics; Estimation of dynamic models.
  • Hidehiko Ichimura, Professor of Economics.  His research focuses on uses of influence function of estimators for a finite dimensional parameter in semiparametric models. In addition, he is working on constructing an econometric framework to link structural life-cycle models to the national transfer accounts via an over-lapping generations model.
  • Thomas G. Kennedy, Ph.D. Professor of Mathematics; Professor of Physics. Monte Carlo simulations; Random walks.
  • Derek M. Lemoine, Ph.D. Assistant Professor of Economics. Decision theory; Bayesian methods; Model epistemology; Complex systems; Real options.
  • Robert S. Maier, Ph.D. Professor of Mathematics; Professor of Physics. Applied probability; Mathematical statistics; Limit laws and large deviation theory; Bioinformatics.
  • Joanna Monti-Masel, D.Phil. Associate Professor of Ecology & Evolutionary Biology. Stochastic processes; Bayesian learning models; Theoretical population genetics; Stochasticity in gene expression.
  • David M. Meko, Ph.D. Associate Research Professor of Dendrochronology. Spectral analysis; ARMA modeling; Time series filtering; Regression.
  • James L. Powell, Professor of Economics, Eller College of Management. His current research focus is on limited dependent variables, endogenous regressors and panel data.
  • Chris Segrin, Ph.D. Professor of Communication; Professor of Psychology; Professor of Family Studies; Head, Department of Communication. Meta-analysis; Longitudinal data analysis; Regression analysis; Dyadic data analysis.
  • Duane L. Sherrill, Ph.D. Professor of Public Health; Associate Dean of Research, Mel and Enid Zuckerman College of Public Health. Longitudinal analyses; Respiratory disease assessment; Applied data analyses; Biometry.
  • Yotam Shmargad, Ph.D. Assistant Professor in the School of Information Resources and Library Science; Impacts of social media on information and market spread in user networks.
  • Subbian Vignesh, Ph.D. Assistant Professor Biomedical Engineering; Software Engineering, Biomedical Data Science and Informatics, Ethics and Professional and Social Responsibility
  • Tiemen Woutersen, Ph.D. Associate Professor of Economics. Econometrics; Causal inference; Duration models; Inferences for partially identified parameters.