Peng Ding Dept of Statistics Statistical causal inference, missing data, Bayesian statistics, applied statistics
Avi Feller Dept of Statistics Goldman School of Public Policy applied statistics, theoretical statistics, Bayesian statistics, machine learning, statistics in social sciences
Ryan Giordano Dept of Statistics machine learning, variational inference, Bayesian methods, robustness quantification, applied statistics
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
Joseph Lewnard School of Public Health infectious diseases, antimicrobial resistance, public health surveillance, mathematical modeling, Bayesian inference
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
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
Nikita Zhivotovskiy Dept of Statistics mathematical statistics, applied probability, statistical learning theory
Adityanand Guntuboyina Dept of Statistics nonparametric and high-dimensional statistics, shape constrained statistical estimation, empirical processes, statistical information theory
Michael Jordan Dept of Statistics Division of Computer Science (EECS) computer science, artificial intelligence, computational biology, statistics, machine learning, electrical engineering, applied statistics, optimization
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
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
Deborah Nolan Dept of Statistics statistics, empirical process, high-dimensional modeling, technology in education
Ryan Tibshirani Dept of Statistics statistical computing, applications in public health, high-dimensional data analysis, nonparametric inference, artificial intelligence, machine learning
Peter Bickel Dept of Statistics statistics, machine learning, semiparametric models, asymptotic theory, hidden Markov models, applications to molecular biology
Amanda Coston Dept of Statistics causal inference, machine learning, nonparametric statistics, responsible AI, algorithmic fairness
Elizabeth Purdom Dept of Statistics computational biology, bioinformatics, statistics, data analysis, sequencing, cancer genomics
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
Yun S. Song Dept of Statistics Division of Computer Science (EECS) computational biology, machine learning, applied probability and statistics
Peng Ding
