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

Division of Electrical Engineering (EECS)

computationally efficient machine learning and deep learning, AI

Dept of Statistics

Division of Computer Science (EECS)

machine learning, statistical learning theory, adaptive control

Jason Lee

Dept of Statistics

Division of Computer Science (EECS)

machine learning theory, optimization, statistics, deep learning

Pieter Abbeel with PR2 robot

Division of Computer Science (EECS)

robotics, machine learning, artificial intelligence, deep learning

Dept of Economics

econometrics, machine learning

Dept of Psychology

attention, curiosity, learning, computational modeling, cognitive development, machine learning, belief formation

Division of Computer Science (EECS)

machine learning, network science, human mobility, public health, graph representation learning

Dept of Neuroscience

behavioral neurophysiology of spatial learning and memory, hippocampus replay, computational models of reinforcement learning and navigationf

Jacob Steinhardt

Jacob Steinhardt

Dept of Statistics

artificial intelligence, machine learning

Tesha Sengupta-Irving

School of Education

STEM education, learning sciences, inequality & resistance, politics of learning, case study & design-based research

Kris D. Gutiérrez

Kris D. Gutiérrez

School of Education

designed learning environments, Cultural dimensions of learning, language and literacy learning for dual language learners, biliteracy, new media literacies, social organization of learning, ethnographic methodology and qualitative approaches to inquiry, design experiment/social design experiments, education of Latino, immigrant, migrant youth, urban education, teacher learning, educational and language policy

School of Education

artificial intelligence, technology, learning, mathematics, science, education, science teaching, gender equity, design of learning environments

Alan H. Schoenfeld

Alan H. Schoenfeld

School of Education

thinking, teaching, learning, productive learning environments, professional development, mathematics education, modeling thinking and decision making

Huiwen Jia

Dept of Industrial Engineering & Operations Research

stochastic and robust optimization, machine learning, online learning algorithms, transportation, revenue management, service system design

Aditi Krishnapriyan

Aditi Krishnapriyan

Dept of Chemical & Biomolecular Engineering

Division of Computer Science (EECS)

machine learning, geometric deep learning, differentiable physics, dynamical systems, numerical methods, computational geometry, optimization

Dan Feldman photo

Dan Feldman

Dept of Neuroscience

neurobiology, learning, neurophysiology, sensory biology

School of Public Health

machine learning, medicine, health policy

Sewon Min

Division of Computer Science (EECS)

natural language processing, machine learning

Division of Computer Science (EECS)

machine learning, society, decision-making

Song Mei

Dept of Statistics

data science, statistics, machine learning

Angjoo Kanazawa

Angjoo Kanazawa

Division of Computer Science (EECS)

CS-vision, graphics, machine learning

School of Education

knowledge representation, adaptive learning, artificial intelligence, learning analytics, Recommender Systems, higher education, data science, Digital Learning Environments, cognitive modeling, Big Data in Education, Knowledge Tracing, Formative Assessment, intelligent tutoring systems, Online Learning, psychometrics, Educational Data Mining

Ali Mesbah

Dept of Chemical & Biomolecular Engineering

model predictive control, learning-based control, low-temperature plasma processing, machine learning and control for plasmas, semiconductor manufacturing

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

Uros Seljak in 2023

Uros Seljak

Dept of Physics

astrophysics, cosmology, machine learning, Bayesian statistics