Find UC Berkeley Faculty

Research Expertise and Interest

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Name

Department

Amanda Coston

Dept of Statistics

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

John Wright

Division of Computer Science (EECS)

quantum state learning, quantum complexity theory, property testing, approximation algorithms

Maya L. Petersen

School of Public Health

Computational Precision Health Program

causal inference, precision health, targeted learning, HIV, global health, pandemics

Alexei Efros

Division of Computer Science (EECS)

computer vision, computer graphics, computational photography, machine learning, artificial intelligence

Jingshen Wang

School of Public Health

precision medicine, causal inference, adaptive experiment, machine learning and artificial intelligence

Bin Yu

Dept of Statistics

machine learning, trustworthy data science and AI, interdisciplinary research in biomedicine, neuroscience, climate science

Susana Chung

School of Optometry

optometry, low vision, vision science, pattern vision, reading, cortical adaptation and plasticity

Michael DeWeese

Dept of Neuroscience

Dept of Physics

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

Ying Cui

Dept of Industrial Engineering & Operations Research

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

Alane Suhr

Division of Computer Science (EECS)

artificial intelligence, natural language processing, machine learning, computer vision, computational linguistics

Irene Chen

Computational Precision Health Program

Division of Computer Science (EECS)

machine learning, personalized medicine and healthcare systems, global health equity, precision health

Nika Haghtalab

Division of Computer Science (EECS)

artificial intelligence, machine learning, theoretical computer science, game theory and mechanism design

Avi Feller

Dept of Statistics

Goldman School of Public Policy

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

Jelani Nelson

Division of Computer Science (EECS)

theory, algorithms, streaming algorithms, dimensionality reduction, randomized algorithms, machine learning, privacy

Armando Fox

Division of Computer Science (EECS)

online education, MOOC, blended learning, parallel programming, software engineering, Web development

Amitai Shenhav

Dept of Psychology

cognitive neuroscience, motivation, decision-making, executive functions, computational modeling

Carlos Norena

Dept of History

Roman history

Gary Karpen

Dept of Molecular & Cell Biology

gene expression, cell biology, chromosome structure and function, drosophila melanogaster, centromere identity and function, biophysics, condensed phases

James W. Rector

Dept of Civil and Environmental Engineering

geoarchaeology, geophysics, acoustics, Seismology, machine learning, energy, carbon capture and storage, oil and gas

Joshua Bloom

Dept of Astronomy

machine learning, gamma-ray bursts, supernovae, time-domain astronomy, data-driven discovery

Khalid M. Mosalam

Dept of Civil and Environmental Engineering

bridges, concrete and masonry structures, damage mechanics, earthquake engineering, fracture mechanics, machine learning

Daniel Siefman

Dept of Nuclear Engineering

neutronics, criticality safety, nuclear data validation, machine learning, neutron noise, reactor dosimetry

Picture of Professor Gray outside the physics department.

Heather Gray

Dept of Physics

particle physics, machine learning, algorithms, quantum algorithms, general purpose computation on the GPU (GPGPU)

David Bamman

School of Information

natural language processing, machine learning, digital humanities, computational social science, data science

Jennifer Chatman

Haas School of Business

innovation, leading change, leveraging organizational culture, leadership assessment, team diversity, narcissistic leaders

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