Researchers in Applied & Theoretical Statistics

Faculty

Researcher Title Research Focus Research Interests
Peter Bartlett Professor Machine Learning
Peter Bickel Professor Emeritus & Professor in the Graduate School
David R Brillinger Professor Applied Statistics, Bioinformatics/Biostatistics, Statistics in Physical Sciences, Theory of Statistics Random process theory and data analysis, risk analysis, spatial-temporal trajectory modeling, sports statistics, applications to ecology, forestry, marine biology, neuroscience, seismology and engineering.
Ching-Shui Cheng Professor Emeritus
Alex D'Amour Neyman Visiting Assistant Professor Applied Statistics, Bayesian Statistics, Machine Learning, Statistics in Social Sciences, Theory of Statistics
Peng Ding Assistant Professor Applied Statistics, Bioinformatics/Biostatistics, Bayesian Statistics, Statistics in Social Sciences causal inference in experiments and observational studies, missing data
Sandrine Dudoit Professor Applied Statistics, Bioinformatics/Biostatistics
Noureddine El Karoui Professor Applied Statistics, Theory of Statistics High-dimensional statistics, random matrices, high-dimensional robust regression, high-dimensional M-estimation, the bootstrap and resampling in high-dimension, limit theorems and statistical inference, applied statistics
Avi Feller Assistant Professor Applied Statistics, Bayesian Statistics, Machine Learning, Statistics in Social Sciences
Will Fithian Assistant Professor
Lisa Goldberg Adjunct Professor Applied Statistics, Bayesian Statistics, Statistics in Social Sciences, Theory of Statistics Financial economics, statistical evaluation of investment strategies, asset allocation, credit and counterparty risk, socially responsible investing
Adityanand Guntuboyina Assistant Professor
Haiyan Huang Associate Professor Applied Statistics, Bioinformatics/Biostatistics High dimensional and integrative genomic data analysis; Network modeling;Hierarchical multi-label classification; translational bioinformatics
Nicholas P. Jewell Professor Bioinformatics/Biostatistics Infectious diseases, specifically HIV; chronic disease epidemiology; envionmental epidemiology; survival analysis; human rights statistics
Michael Jordan Professor
Oscar Hernan Madrid Padilla Neyman Visiting Assistant Professor Applied Statistics, Bayesian Statistics, Machine Learning, Theory of Statistics
Jon McAuliffe Adjunct Associate Professor Applied Statistics, Machine Learning, Statistics in Physical Sciences machine learning, statistical prediction, variational inference, statistical computing, optimization
Rasmus Nielsen Professor Bioinformatics/Biostatistics Statistical Genomics, Theoretical Population Genetics
Deborah Nolan Professor and Chair
Christopher Paciorek Adjunct Professor Applied Statistics, Bayesian Statistics environmental statistics, statistical computing, spatial statistics, Bayesian statistics
Sam Pimentel Assistant Professor Applied Statistics, Bioinformatics/Biostatistics, Statistics in Social Sciences
Elizabeth Purdom Associate Professor Applied Statistics, Bioinformatics/Biostatistics
John Rice Professor Emeritus
Gaston Sanchez Lecturer Applied Statistics, Statistics in Social Sciences Dimension reduction techniques and component-based methods
Jasjeet Sekhon Professor Applied Statistics, Statistics in Social Sciences
Juliet Shaffer Teaching Professor Emerita
Yun S. Song Professor Applied Statistics, Bioinformatics/Biostatistics Computational biology, statistical genetics, applied probability
Terry Speed Professor Emeritus Bioinformatics/Biostatistics The application of statistics to genetics and genomics, and to related fields such as proteomics, metabolomics and epigenomics.
Philip B. Stark Professor Applied Statistics, Statistics in Physical Sciences, Statistics in Social Sciences uncertainty quantification and inference, inverse problems, nonparametrics, risk assessment, earthquake prediction, election auditing, geomagnetism, cosmology, litigation, food/nutrition
Chuck Stone Professor Emeritus The stability and sustainability of the worldwide economy in the first half of the twenty-first century and, especially, its lack thereof. One possible result of unsustainability is a transition to a decent sustainable state; another is collapse.
Bernd Sturmfels Professor Algebraic Statistics
Aram Thomasian Professor Emeritus
Mark van der Laan Professor
Ken Wachter Professor Statistics in Social Sciences Mathematical demography, models for the evolution of aging, simulation.
Martin Wainwright Professor
Bin Yu Professor Applied Statistics, Bioinformatics/Biostatistics, Machine Learning, Theory of Statistics Statistical inference for high dimensional data and interdisciplinary research in neuroscience, remote sensing, and text summarization.

Postdocs

Researcher Title Research Focus Research Interests
Nicholas Michaud Postdoctoral Scholar (joint ESPM) Applied Statistics, Bayesian Statistics
Dao Nguyen Postdoctoral Scholar (joint ESPM) Bayesian Statistics, Machine Learning MCMC, Partially Observed Markov Process, Intractable likelihood inference, Stochastic Optimization
Aaditya Ramdas Postdoctoral Scholar Machine Learning, Theory of Statistics
Farbod (Fred) Roosta-Khorasani Postdoctoral Scholar Applied Statistics, Machine Learning Randomized Algorithms, Numerical Linear Algebra, Numerical Optimization, Numerical Analysis and Scientific Computing, Mathematical Statistics, Image Processing and Inverse Problems
Shusen Wang Postdoc Machine Learning machine learning, randomized numerical linear algebra

Graduate Students

Researcher Dissertation Advisor Research Focus
Nicholas Altieri Machine Learning
Rebecca Barter Bin Yu
Eli Ben-Michael
Jade Benjamin-Chung Bioinformatics/Biostatistics
Joseph Borja
Emily Chang Bioinformatics/Biostatistics
Kathryn (Benton) Colborn Statistical models for longitudinal analysis of single and mixed species infections Terry Speed Bioinformatics/Biostatistics
Jeremy Coyle Alan Hubbard Bioinformatics/Biostatistics
Anna Decker Semiparametric, prediction, variable importance, and longitudinal causal effect estimation in critical care Alan Hubbard Bioinformatics/Biostatistics, Machine Learning
Stephanie DeGraaf Bioinformatics/Biostatistics
Iván Díaz Causal inference methods for continuous exposures Mark van der Laan Bioinformatics/Biostatistics, Machine Learning, Theory of Statistics
Keenan Fenton Bioinformatics/Biostatistics
Arturo Fernandez Jon McAuliffe and Philip Stark Applied Statistics, Machine Learning, Statistics in Physical Sciences
Jonathan Fischer Yun S. Song Bioinformatics/Biostatistics, Machine Learning, Statistics in Physical Sciences, Theory of Statistics
Ryan Giordano Michael Jordan Applied Statistics, Bayesian Statistics, Machine Learning, Statistics in Physical Sciences
Geno Guerra Yun S. Song and Rasmus Nielsen Applied Statistics, Bioinformatics/Biostatistics
Curt Hansen Sandrine Dudoit Bioinformatics/Biostatistics, Machine Learning
Chun Yu Hong (Johnny) Will Fithian and Perry de Valpine Applied Statistics, Bioinformatics/Biostatistics
Steve Howard Jasjeet Sekhon & Jon McAuliffe
Miyabi Ishihara
Marla Johnson Elizabeth Purdom Bioinformatics/Biostatistics
Sören Künzel Bickel, Sekhon, Yu Applied Statistics, Machine Learning, Statistics in Social Sciences, Theory of Statistics
Karl Kumbier Bin Yu Applied Statistics, Bioinformatics/Biostatistics, Machine Learning
Lihua Lei
Sam Lendle Mark van der Laan Bioinformatics/Biostatistics
Jingyi Jessica Li Statistical Methods for Analyzing High-Throughput Genomic Data Peter J. Bickel & Haiyan Huang Bioinformatics/Biostatistics
Runjing (Bryan) Liu Applied Statistics, Bayesian Statistics, Machine Learning
Kevin McLoughlin Modeling and Analysis of Oligonucleotide Microarray Data for Pathogen Detection Terry Speed Bioinformatics/Biostatistics, Machine Learning
Jarrod Millman Bioinformatics/Biostatistics
Soumendu Sundar Mukherjee
Jamie Murdoch Machine Learning
Kellie Ottoboni Philip Stark
Lucia Petito Bioinformatics/Biostatistics
Yannik Pitcan Peter Bartlett Bayesian Statistics, Machine Learning
Steven Pollack Bioinformatics/Biostatistics
Sujayam Saha Bin Yu, Aditya Guntuboyina Machine Learning, Theory of Statistics
Oleg Sofrygin Causal Inference Mark van der Laan Bioinformatics/Biostatistics
Jake Soloff Bayesian Statistics, Machine Learning, Theory of Statistics
Sara Stoudt Will Fithian and Perry de Valpine
Kelly Street Sandrine Dudoit Applied Statistics, Bioinformatics/Biostatistics
Vanessa Viggiano Bioinformatics/Biostatistics
Yu Wang Machine Learning, Theory of Statistics
Andre Kurepa Waschka Alan Hubbard and Mark van der Laan Bioinformatics/Biostatistics
Yuting Wei Martin Wainwright, Adityanand Guntuboyina Machine Learning, Theory of Statistics
Chelsea Zhang Bayesian Statistics, Machine Learning