Find UC Berkeley Faculty

Research Expertise and Interest

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Name

Department

Composites, additive manufacturing, in-situ monitoring and process control, artificial intelligence and machine learning, bioinspired materials

Bin Yu

Dept of Statistics

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

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

Irene Chen

Computational Precision Health Program

Division of Computer Science (EECS)

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

Ying Cui

Dept of Industrial Engineering & Operations Research

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

Avi Feller

Dept of Statistics

Goldman School of Public Policy

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

Armando Fox

Division of Computer Science (EECS)

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

Teresa Head-Gordon

Dept of Bioengineering

Dept of Chemical & Biomolecular Engineering

Dept of Chemistry

Computational chemistry, machine learning, chemical physics, biophysics, biomolecules, materials, catalysis, computational science

Dor Abrahamson

School of Education

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

Daniel Siefman

Dept of Nuclear Engineering

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

Jelani Nelson

Division of Computer Science (EECS)

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

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

Dana Miller-Cotto

School of Education

educational equity, early childhood education, cognitive processes, early math learning, social contexts of education

Michael Jordan

Dept of Statistics

Division of Computer Science (EECS)

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

Jabari Mahiri

School of Education

language, culture, society, literacy, literacy learning of urban youth, African American students in schools, writing development, effective teaching, learning strategies in multicultural urban schools and communities, studies of race - class - and gender, Leaders for Equity and Democracy EdD - LEAD

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

Stuart J. Russell

Division of Computer Science (EECS)

artificial intelligence, computational biology, algorithms, machine learning, real-time decision-making, probabilistic reasoning

Panayiotis Papadopoulos

Dept of Mechanical Engineering

continuum mechanics, computational mechanics, contact mechanics, computational plasticity, materials modeling, solid mechanics, applied mathematics, dynamics of pseudo-rigid bodies

Adrian Aguilera

Computational Precision Health Program

School of Social Welfare

digital health, depression interventions, cognitive behavioral therapy, health equity, machine learning, implementation science

Peter Bickel

Dept of Statistics

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

Bethany L. Goldblum

Dept of Nuclear Engineering

applied nuclear physics, neutron detection, scintillation physics, machine learning applications, nuclear weapon policy

Ryan Tibshirani

Dept of Statistics

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

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