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
Nikita Zhivotovskiy Dept of Statistics mathematical statistics, applied probability, statistical learning theory
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
Adityanand Guntuboyina Dept of Statistics nonparametric and high-dimensional statistics, shape constrained statistical estimation, empirical processes, statistical information theory
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
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
Michael Jordan Dept of Statistics Division of Computer Science (EECS) computer science, artificial intelligence, computational biology, statistics, machine learning, electrical engineering, applied statistics, optimization
Perry de Valpine Dept of Environmental Science, Policy & Management population ecology, mathematical modeling and statistics
Yun S. Song Dept of Statistics Division of Computer Science (EECS) computational biology, machine learning, applied probability and statistics
Joseph Lewnard School of Public Health infectious diseases, antimicrobial resistance, public health surveillance, mathematical modeling, Bayesian inference
Deborah Nolan Dept of Statistics statistics, empirical process, high-dimensional modeling, technology in education
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
Elizabeth Purdom Dept of Statistics computational biology, bioinformatics, statistics, data analysis, sequencing, cancer genomics
Ahmed Alaa Computational Precision Health Program machine learning and artificial intelligence, health care, statistics
Amanda Coston Dept of Statistics causal inference, machine learning, nonparametric statistics, responsible AI, algorithmic fairness
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
Samuel Lucas Dept of Sociology research methods, demography, sociology, social stratification, sociology of education, research statistics
Anil Aswani Dept of Industrial Engineering & Operations Research machine learning and artificial intelligence, precision health, optimization, statistics
Peter Bickel Dept of Statistics statistics, machine learning, semiparametric models, asymptotic theory, hidden Markov models, applications to molecular biology
Peng Ding
Peng Ding
Peng Ding
