Find UC Berkeley Faculty

Research Expertise and Interest

Use quotes to search for an exact phrase. Example: "computational biology"

Name

Department

Peng Ding

Dept of Statistics

Statistical causal inference, missing data, Bayesian statistics, applied statistics

NikitaZhivotovskiy

Nikita Zhivotovskiy

Dept of Statistics

mathematical statistics, applied probability, statistical learning theory

School of Public Health

causal inference, targeted learning, statistical issues in epidemiology, precision medicine and public health

Ryan Tibshirani giving a whiteboard talk

Ryan Tibshirani

Dept of Statistics

statistical computing, applications in public health, high-dimensional data analysis, nonparametric inference, artificial intelligence, machine learning

Adityanand Guntuboyina

Adityanand Guntuboyina

Dept of Statistics

nonparametric and high-dimensional statistics, shape constrained statistical estimation, empirical processes, statistical information theory

Sandrine Dudoit

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

Dept of Statistics

Division of Computer Science (EECS)

machine learning, statistical learning theory, adaptive control

Jennifer Listgarten

Jennifer Listgarten

Division of Computer Science (EECS)

artificial intelligence, machine learning, computational biology, protein engineering, statistical design of experiments, statistical machine learning, experimental design

Fei Xu

Dept of Psychology

cognitive development, language development, learning mechanisms, statistical learning and statistical inference, conceptual development, developmental psychology, word learning, physical reasoning, social cognition in infants and children, learning in infants and young children, computational models of cognitive development, Bayesian probabilistic models, cognitive development and AI models, psychology and philosophy

Dept of Statistics

causal inference, machine learning, nonparametric statistics, responsible AI, algorithmic fairness

Dept of Statistics

machine learning, variational inference, Bayesian methods, robustness quantification, applied statistics

Shirshendu Ganguly

Shirshendu Ganguly

Dept of Statistics

probability theory, statistical mechanics

Michael DeWeese

Dept of Neuroscience

Dept of Physics

machine learning, computation, systems neuroscience, auditory cortex, neural coding, statistical mechanics

Dept of Statistics

probability, mathematical probability, statistical mechanics

Ying Cui

Dept of Industrial Engineering & Operations Research

continuous optimization, optimization under uncertainty, statistical estimations, machine learning, artificial intelligence

Lexin Li

School of Public Health

neuroimaging data analysis, deep brain stimulation, brain-computer-interface, statistical machine learning, deep learning, reinforcement learning, networks data analysis, functional data analysis, tensor analysis, ordinary differential equations, dimension reduction, high dimensional inference

Dept of Political Science

political economy, ethnic politics, comparative clientelism in developing countries, research design, causal inference, statistical methods, multi-method research

Vadim Gorin with book "Probability" by Albert Shiryaev

Vadim Gorin

Dept of Mathematics

Dept of Statistics

integrable probability, random matrices, asymptotic representation theory, 2d statistical mechanics, interacting particle systems, high-dimensional statistics

Andrew Bray

Dept of Statistics

statistical computing, data privacy, data science

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

Haas School of Business

labor markets, human resources, data analysis and statistical methods

Jason Lee

Dept of Statistics

Division of Computer Science (EECS)

machine learning theory, optimization, statistics, deep learning

Nilah Ioannidis

Nilah Ioannidis

Division of Computer Science (EECS)

computational biology, machine learning, artificial intelligence, genomics, personal genome interpretation, precision health, rare diseases, statistical genetics, molecular biology, biophysics

Oskar Hallatschek

Oskar Hallatschek

Dept of Physics

biophysics, evolutionary dynamics, soft matter, statistical physics, theory and experiments

Avi Feller

Dept of Statistics

Goldman School of Public Policy

applied statistics, theoretical statistics, Bayesian statistics, machine learning, statistics in social sciences