Find UC Berkeley Faculty

Research Expertise and Interest

Search by keyword or research area. Use quotes for exact phrases — e.g., "computational biology".

Name

Department

Dept of Statistics

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

NikitaZhivotovskiy

Nikita Zhivotovskiy

Dept of Statistics

mathematical statistics, applied probability, statistical learning theory

Dept of Statistics

probability, mathematical probability, statistical mechanics

Shirshendu Ganguly

Shirshendu Ganguly

Dept of Statistics

probability theory, statistical mechanics

Adityanand Guntuboyina

Adityanand Guntuboyina

Dept of Statistics

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

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

Steven N. Evans

Dept of Mathematics

Dept of Statistics

large random combinatorial structures, random matrices, superprocesses & other measure-valued processes, probability on algebraic structures -particularly local fields, applications of stochastic processes to biodemography, mathematical finance, population genetics, phylogenetics & historical linguistics

Song Mei

Dept of Statistics

data science, statistics, machine learning

Dept of Statistics

fragmentation, statistics, mathematics, Brownian motion, distribution theory, path transformations, stochastic processes, local time, excursions, random trees, random partitions, processes of coalescence

Perry de Valpine

Perry de Valpine

Dept of Environmental Science, Policy & Management

population ecology, mathematical modeling and statistics

Sandya Subramanian

Computational Precision Health Program

translational medicine, computational neuroscience, physiology, statistics, mathematical modeling

Avi Feller

Dept of Statistics

Goldman School of Public Policy

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

Peng Ding

Dept of Statistics

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

Ilan Adler

Dept of Industrial Engineering & Operations Research

mathematical programming, computational game theory, applied probability

Franziska Weber

Franziska Weber

Dept of Mathematics

applied mathematics, mathematical analysis, numerical analysis, nonlinear partial differential equations

Dept of Statistics

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

School of Education

mathematical cognition, design-based research, mixed-media design for mathematics learning environments, embodied interaction

Anil Aswani in outside setting

Anil Aswani

Dept of Industrial Engineering & Operations Research

machine learning and artificial intelligence, precision health, optimization, statistics

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

Ayesha S. Mahmud

Ayesha S. Mahmud

Dept of Demography

Infectious disease dynamics, disease ecology, mathematical models, Asia, Africa, Central America, climate change

Jennifer Chayes

Jennifer Chayes

Dept of Mathematics

Dept of Statistics

Division of Computer Science (EECS)

phase transitions in computer science, structural and dynamical properties of networks, graphons, machine learning, ethical decision making, climate change

Dept of Mathematics

mathematics, algebraic geometry, commutative algebra, computation

Steven Kahn

Dept of Astronomy

Dept of Physics

astrophysics, cosmology, optical astrophysics

Dept of Statistics

Division of Computer Science (EECS)

machine learning, statistical learning theory, adaptive control

Mark van der Laan

Dept of Statistics

School of Public Health

targeted learning, real-world data integration in RCTs, sequential adaptive designs, computational biology and genomics, censored data and survival analysis, medical research, inference in longitudinal studies