Samuel Lucas Dept of Sociology research methods, demography, sociology, social stratification, sociology of education, research statistics
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
Nikita Zhivotovskiy Dept of Statistics mathematical statistics, applied probability, statistical learning theory
Aaron Fisher Dept of Psychology Idiographic Science, Group-to-Individual Generalizability, Personalization, EMA, Time Series, physiology, Methods and Statistics
Avi Feller Dept of Statistics Goldman School of Public Policy applied statistics, theoretical statistics, Bayesian statistics, machine learning, statistics in social sciences
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
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
Alexandre Mas Haas School of Business labor markets, human resources, data analysis and statistical methods
Thad Dunning Dept of Political Science political economy, ethnic politics, comparative clientelism in developing countries, research design, causal inference, statistical methods, multi-method research
Yun S. Song Dept of Statistics Division of Computer Science (EECS) computational biology, machine learning, applied probability and statistics
Sophia Rabe-Hesketh School of Education biostatistics, educational statistics, latent variable models, missing data methods, multilevel models, generalized linear latent and mixed models, hierarchical models, longitudinal data, Item response models, structural equation models
Deborah Nolan Dept of Statistics statistics, empirical process, high-dimensional modeling, technology in education
Ahmed Alaa Computational Precision Health Program machine learning and artificial intelligence, health care, statistics
Elizabeth Purdom Dept of Statistics computational biology, bioinformatics, statistics, data analysis, sequencing, cancer genomics
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
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
Patrick Bradshaw School of Public Health epidemiologic methods, Bayesian methods, cancer epidemiology, cardiometabolic risk
Amanda Coston Dept of Statistics causal inference, machine learning, nonparametric statistics, responsible AI, algorithmic fairness
Peter Bickel Dept of Statistics statistics, machine learning, semiparametric models, asymptotic theory, hidden Markov models, applications to molecular biology
Samuel Lucas
Samuel Lucas
Samuel Lucas
