Xueyin (Snow) Zhang Dept of Philosophy Bayesian epistemology, decision theory, philosophy of probability, Chinese philosophy
Patrick Bradshaw School of Public Health epidemiologic methods, Bayesian methods, cancer epidemiology, cardiometabolic risk
Peng Ding Dept of Statistics Statistical causal inference, missing data, Bayesian statistics, applied statistics
Ryan Giordano Dept of Statistics machine learning, variational inference, Bayesian methods, robustness quantification, applied statistics
Avi Feller Dept of Statistics Goldman School of Public Policy applied statistics, theoretical statistics, Bayesian statistics, machine learning, statistics in social sciences
Joseph Lewnard School of Public Health infectious diseases, antimicrobial resistance, public health surveillance, mathematical modeling, Bayesian inference
Philip Marcus Dept of Mechanical Engineering algorithms, fluid mechanics, nonlinear dynamics, atmospheric flows, convection, ocean flows, numerical analysis, wind energy, Bayesian optimization, neural networks, turbulence, planet formation, internal gravity waves, inertial waves, desalination, protoplanetary disks
Alper Atamturk Dept of Industrial Engineering & Operations Research sparse learning, integer programming, computational optimization, robust optimization, logistics
Jimmy A. McGuire Dept of Integrative Biology historical biogeography, evolutionary biology, Southeast Asia, population genetics, hummingbirds, functional morphology, vertebrate systematics, phylogenetic analysis, life history evolution, Bayesian methods, Southeast Asian flying lizards
William (Bill) D. Thompson Dept of Psychology cognition, cognitive science, artificial intelligence, learning, Problem solving, Reasoning, decision-making, Bayesian statistics, natural language processing, machine learning, computational modeling, collective decision-making, social networks
Paul Grigas Dept of Industrial Engineering & Operations Research optimization, machine learning, data-driven decision-making
Javad Lavaei Dept of Industrial Engineering & Operations Research control theory, optimization, power systems
Ying Cui Dept of Industrial Engineering & Operations Research continuous optimization, optimization under uncertainty, statistical estimations, machine learning, artificial intelligence
Thibaut Mastrolia Dept of Industrial Engineering & Operations Research stochastic control, game theory, finance, optimization
Ming Gu Dept of Mathematics mathematics, scientific computing, numerical linear algebra, convex optimization
Prasad Raghavendra Division of Computer Science (EECS) theory(THY), optimization, complexity theory, approximation algorithms
Dorit Hochbaum Dept of Industrial Engineering & Operations Research data mining, integer programming, discrete optimization, network flow techniques, clustering, image segmentation, machine vision, pattern recognition
Sam Pimentel Dept of Statistics causal inference, health services & policy analysis, biostatistics, discrete optimization
Carl Boettiger Dept of Environmental Science, Policy & Management theoretical ecology, stochastic processes, optimal control, decision theory, ecoinformatics, data science, tipping points
Scott Moura Dept of Civil and Environmental Engineering control systems, optimization, data science, batteries, electric vehicles, energy systems
Michael J. Lindsey Dept of Mathematics applied mathematics, mathematical analysis, probability, numerical analysis, optimization, Monte Carlo methods
Satish Rao Division of Computer Science (EECS) combinatorial optimization, design and analysis of algorithms
Duncan Callaway Dept of Energy & Resources Group Division of Electrical Engineering (EECS) energy systems analysis, grid decarbonization, modeling and control and optimization for electric power systems
Uros Seljak
