Find UC Berkeley Faculty

Research Expertise and Interest

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Name

Department

Nikita Zhivotovskiy

Dept of Statistics

mathematical statistics, applied probability, statistical learning theory

Peter Bartlett

Dept of Statistics

Division of Computer Science (EECS)

machine learning, statistical learning theory, adaptive control

Adityanand Guntuboyina

Dept of Statistics

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

Shirshendu Ganguly

Dept of Statistics

probability theory, statistical mechanics

Jennifer Listgarten

Division of Computer Science (EECS)

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

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

Peng Ding

Dept of Statistics

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

Michael DeWeese

Dept of Neuroscience

Dept of Physics

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

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, cognitive development and AI models, psychology and philosophy

Christian Borgs

Division of Computer Science (EECS)

theoretical computer science, probability theory, combinatorics, complex networks, statistical physics, artificial intelligence, applications of artificial intelligence and machine learning in engineering and sciences

Kannan Ramchandran

Division of Computer Science (EECS)

Division of Electrical Engineering (EECS)

statistical and sparse signal processing, adversarial and distributed machine learning, coded computing, privacy and security, scalable distributed video-on-demand delivery, coding theory, communications, information theory, peer-to-peer networking, blockchains

Alan Hubbard

School of Public Health

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

Ying Cui

Dept of Industrial Engineering & Operations Research

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

Ryan Tibshirani

Dept of Statistics

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

Peter Bickel

Dept of Statistics

statistics, machine learning, semiparametric models, asymptotic theory, hidden Markov models, applications to molecular biology

Oskar Hallatschek

Dept of Physics

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

Song Mei

Dept of Statistics

data science, statistics, machine learning

Negar Mehr

Dept of Mechanical Engineering

robotics, control theory, artificial intelligence, game theory, machine learning

Avi Feller

Dept of Statistics

Goldman School of Public Policy

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

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

Alan Hammond

Dept of Statistics

probability, mathematical probability, statistical mechanics

Yun S. Song

Dept of Statistics

Division of Computer Science (EECS)

computational biology, machine learning, applied probability and statistics

Shachar Kariv

Dept of Economics

economics, experimental economics, behavioral economics, networks, microeconomic theory, social learning

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

Michael Jordan

Dept of Statistics

Division of Computer Science (EECS)

computer science, artificial intelligence, computational biology, statistics, machine learning, electrical engineering, applied statistics, optimization

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