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Main menu

  • Research Highlights
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  • Research Units
  • How to
    • Secure Funding
      • Contracts, Gifts and Grants
      • Industry Consortia
      • Funding Opportunities
      • UCB Grant Life Cycle
      • Berkeley Research Development Office
      • Impacts of 2025 Federal Executive Orders and Directives
    • Ensure Compliance
      • Research Policies & Administration
      • Research Compliance
      • Intellectual Property & Tech Transfer
      • Research Personnel
      • Field and International Research
    • Locate Facilities
      • Core Facilities
      • Berkeley Research Infrastructure Commons (RIC)
      • Research Computing and Data Management
      • Field Stations, Research Forests, and Museums
    • For VCR Units
      • ORU Policies
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      • VCRO HR Resources

Utilities navigation

  • About Us
    • Vice Chancellor Yelick
    • Associate Vice Chancellor Siu
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Find UC Berkeley Faculty

Use quotes to search for an exact phrase. Example: "computational biology"
Peng Ding Peng Ding
Dept of Statistics
Statistical causal inference, missing data, Bayesian statistics, applied statistics
Karthik Shekhar Karthik Shekhar
Dept of Chemical & Biomolecular Engineering
cellular and systems biology, statistical inference, single-cell genomics
Alan Hubbard Alan Hubbard
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
Thad Dunning Thad Dunning
Dept of Political Science
political economy, ethnic politics, comparative clientelism in developing countries, research design, causal inference, statistical methods, multi-method research
Nikita Nikita Zhivotovskiy
Dept of Statistics
mathematical statistics, applied probability, statistical learning theory
headshot of Amanda Coston Amanda Coston
Dept of Statistics
causal inference, machine learning, nonparametric statistics, responsible AI, algorithmic fairness
headshot of Ryan Giordano Ryan Giordano
Dept of Statistics
machine learning, variational inference, Bayesian methods, robustness quantification, applied statistics
Fei Xu 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
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
Shirshendu Ganguly Shirshendu Ganguly
Dept of Statistics
probability theory, statistical mechanics
Erin Hartman Erin Hartman
Dept of Political Science
causal inference, survey data analysis
Alan Hammond Alan Hammond
Dept of Statistics
probability, mathematical probability, statistical mechanics
Sam Pimentel Sam Pimentel
Dept of Statistics
causal inference, health services & policy analysis, biostatistics, discrete optimization
Lexin Li 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
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
Peter Barlett Peter Bartlett
Dept of Statistics
Division of Computer Science (EECS)
machine learning, statistical learning theory, adaptive control
headshot of Alistair Sinclair 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
Jingshen Wang Jingshen Wang
School of Public Health
Precision Medicine, causal inference, adaptive experiment, machine learning and artificial intelligence
Maya Petersen Maya L. Petersen
School of Public Health
Computational Precision Health Program
causal inference, precision health, targeted learning, HIV, global health, pandemics
headshot of Alexandre Mas Alexandre Mas
Haas School of Business
labor markets, human resources, data analysis and statistical methods
Joseph Lewnard Joseph Lewnard
School of Public Health
infectious diseases, antimicrobial resistance, public health surveillance, mathematical modeling, Bayesian inference
Zonszein profile picture Stephanie Zonszein
Dept of Political Science
immigrant integration, intergroup relations, causal inference, race and ethnic politics, political behavior
Oskar Hallatschek Oskar Hallatschek
Dept of Physics
biophysics, evolutionary dynamics, soft matter, statistical physics, theory and experiments
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University of California, Berkeley

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