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
Adityanand Guntuboyina Dept of Statistics nonparametric and high-dimensional statistics, shape constrained statistical estimation, empirical processes, statistical information 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
Avi Feller Dept of Statistics Goldman School of Public Policy applied statistics, theoretical statistics, Bayesian statistics, machine learning, statistics in social sciences
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
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
Ahmed Alaa Computational Precision Health Program machine learning and artificial intelligence, health care, statistics
Yun S. Song Dept of Statistics Division of Computer Science (EECS) computational biology, machine learning, applied probability and statistics
Deborah Nolan Dept of Statistics statistics, empirical process, high-dimensional modeling, technology in education
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
Ryan Giordano Dept of Statistics machine learning, variational inference, Bayesian methods, robustness quantification, applied statistics
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
Peter Bickel Dept of Statistics statistics, machine learning, semiparametric models, asymptotic theory, hidden Markov models, applications to molecular biology
Jennifer Listgarten Division of Computer Science (EECS) artificial intelligence, machine learning, computational biology, protein engineering, statistical design of experiments, statistical machine learning, experimental design
Aaron Fisher Dept of Psychology Idiographic Science, Group-to-Individual Generalizability, Personalization, EMA, Time Series, physiology, Methods and Statistics
Peter Bartlett Dept of Statistics Division of Computer Science (EECS) machine learning, statistical learning theory, adaptive control
Peng Ding
Peng Ding
Peng Ding
