Deborah Nolan Dept of Statistics statistics, empirical process, high-dimensional modeling, technology in education
Adityanand Guntuboyina Dept of Statistics nonparametric and high-dimensional statistics, shape constrained statistical estimation, empirical processes, statistical information theory
Nikita Zhivotovskiy Dept of Statistics mathematical statistics, applied probability, statistical learning theory
Ryan Tibshirani Dept of Statistics statistical computing, applications in public health, high-dimensional data analysis, nonparametric inference, artificial intelligence, machine learning
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
Perry de Valpine Dept of Environmental Science, Policy & Management population ecology, mathematical modeling 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
Amanda Coston Dept of Statistics causal inference, machine learning, nonparametric statistics, responsible AI, algorithmic fairness
Deborah Nolan
Deborah Nolan
Deborah Nolan
