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Professor
Emmanuel J. Candès
harmonic analysis
high-dimensional statistics
signal processing
information theory
Sourav Chatterjee
probability theory
Amir Dembo
probability theory
information theory
stochastic processes
Persi Diaconis
probability theory
Bayesian statistics
statistical computing
combinatorics
David Donoho
harmonic analysis
signal processing
deep learning
compressed sensing
Bradley Efron
bootstrap
biostatistics
Bayesian statistics
Emily B. Fox
machine learning
time series
machine learning for health
computational neuroscience
Trevor J. Hastie
nonparametric regression
statistical computing
data mining
Susan Holmes
phylogenetic trees
computational statistics
bootstrap
nonparametric computer intensive methods
multivariate analysis
data mining
Iain Johnstone
biostatistics
decision theory
estimation theory
asymptotics
signal processing
Tze Leung Lai
stochastic optimization
empirical Bayes modeling
quantitative finance
multivariate analysis
time series
probability theory
stochastic processes
biostatistics
Andrea Montanari
Associate Chair
high-dimensional statistics
mass spectrometry algorithms
graphical models
Art B. Owen
Department Chair
empirical likelihood
Monte Carlo
bioinformatics
Joseph P. Romano
bootstrap
subsampling and resampling methods
multiple hypothesis testing
large sample theory
econometrics
Chiara Sabatti
Bayesian statistics
computational biology
statistical genetics
David O. Siegmund
probability theory
genetic mapping
nonlinear regression
Jonathan Taylor
Gaussian processes
differential geometric methods
Robert Tibshirani
biostatistics
data mining
Guenther Walther
mixture analysis
flow cytometry
astrophysics
computational statistics
Wing Hung Wong
computational biology
multivariate analysis
statistical inference
machine learning
Professor Emeritus
Jerome H. Friedman
machine learning
data mining
Paul Switzer
space-time statistics
trend detection
monitoring design
Assistant Professor
John Duchi
machine learning
information theory
stochastic optimization
Scott Linderman
machine learning
computational neuroscience
Tengyu Ma
machine learning
deep learning
high-dimensional statistics
optimization
Julia Palacios
Gaussian processes
graphical models
statistical genetics
Bayesian statistics
evolutionary genomics
Dominik Rothenhäusler
causal inference
distributional robustness
high-dimensional statistics
graphical models
heterogeneous data
Tselil Schramm
algorithms
optimization
machine learning
computational statistics
high-dimensional statistics
Courtesy Professor
John Ioannidis
clinical trials
meta-analysis
Hua Tang
statistical genetics
computational biology
population genomics
Lu Tian
personalized medicine
randomized clinical trials
survival analysis
meta-analysis
Courtesy Associate Professor
Percy Shuo Liang
machine learning
natural language processing
David Rogosa
statistics in behavioral sciences
longitudinal research
educational assessment
Stefan Wager
causal inference
machine learning
Courtesy Assistant Professor
Mike Baiocchi
causal inference
Adjunct Professor
John Chambers
statistical computing
data science
data visualization
Lester Mackey
high-dimensional statistics
machine learning
algorithms
Jacqueline Meulman
nonlinear multivariate analysis
Senior Research Scientist
Balasubramanian Narasimhan
statistical computing
bioinformatics
machine learning
clinical trials
