Adityanand Guntuboyina Dept of Statistics nonparametric and high-dimensional statistics, shape constrained statistical estimation, empirical processes, statistical information theory
Peng Ding Dept of Statistics Statistical causal inference, missing data, Bayesian statistics, applied statistics
Nikita Zhivotovskiy Dept of Statistics mathematical statistics, applied probability, statistical learning theory
Sean Gailmard Dept of Political Science American political institutions, bureaucratic organizations, executive branch, public administration, political economy, statistical modeling
Perry de Valpine Dept of Environmental Science, Policy & Management population ecology, mathematical modeling and statistics
Deborah Nolan Dept of Statistics statistics, empirical process, high-dimensional modeling, technology in education
Sandrine Dudoit Dept of Statistics School of Public Health statistics, machine learning, data science, applied statistics, statistical computing, computational biology, computational genomics, precision medicine, precision health
Sandya Subramanian Computational Precision Health Program translational medicine, computational neuroscience, physiology, statistics, mathematical modeling
Vadim Gorin Dept of Mathematics Dept of Statistics integrable probability, random matrices, asymptotic representation theory, 2d statistical mechanics, interacting particle systems, high-dimensional statistics
Jennifer Listgarten Division of Computer Science (EECS) artificial intelligence, machine learning, computational biology, protein engineering, statistical design of experiments, statistical machine learning, experimental design
Peter Bartlett Dept of Statistics Division of Computer Science (EECS) machine learning, statistical learning theory, adaptive control
Haiyan Huang Dept of Statistics applied statistics, functional genomics, translational bioinformatics, high dimensional and integrative genomic/genetic data analysis, network modeling, hierarchical multi-lable classification
Alistair Sinclair Dept of Statistics Division of Electrical Engineering (EECS) algorithms, applied probability, statistics, random walks, Markov chains, computational applications of randomness, Markov chain Monte Carlo, statistical physics, combinatorial optimization
Alexandre Mas Haas School of Business labor markets, human resources, data analysis and statistical methods
Daniel McFadden Dept of Economics latent variable models, choice modeling, econometric modeling, sampling theory, production theory, consumer theory
Oskar Hallatschek Dept of Physics biophysics, evolutionary dynamics, soft matter, statistical physics, theory and experiments
Alan Hubbard School of Public Health causal inference, targeted learning, statistical issues in epidemiology, precision medicine and public health
Brian A. Barsky Division of Computer Science (EECS) School of Optometry computer science, geometric design and modeling, computer graphics, computer aided cornea modeling and visualization, medical imaging, virtual environments for surgical simulation
Ryan Tibshirani Dept of Statistics statistical computing, applications in public health, high-dimensional data analysis, nonparametric inference, artificial intelligence, machine learning
Michael DeWeese Dept of Neuroscience Dept of Physics machine learning, computation, systems neuroscience, auditory cortex, neural coding, statistical mechanics
Sanjay Govindjee Dept of Civil and Environmental Engineering finite element analysis, Theoretical and computational solid mechanics, constitutive theory, micromechanics, polymer mechanics, elastomer modeling, battery modeling, thermomechanics, continuum mechanics, failure analysis
Anne Collins Dept of Psychology learning, decision making, computational modeling, executive functions
Adityanand Guntuboyina
Adityanand Guntuboyina
Adityanand Guntuboyina
