Find UC Berkeley Faculty

Research Expertise and Interest

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Name

Department

Tesha Sengupta-Irving

School of Education

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

Avi Feller

Dept of Statistics

Goldman School of Public Policy

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

Christian Borgs

Division of Computer Science (EECS)

theoretical computer science, probability theory, combinatorics, complex networks, statistical physics, artificial intelligence, applications of artificial intelligence and machine learning in engineering and sciences

Marcia C. Linn

School of Education

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

Song Mei

Dept of Statistics

data science, statistics, machine learning

Emma Pierson

Division of Computer Science (EECS)

data science, machine learning, inequality, Healthcare

Benjamin Recht

Division of Computer Science (EECS)

machine learning, data science, artificial intelligence

Laura Kwong

School of Public Health

environmental health sciences

Bin Yu

Dept of Statistics

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

Diag Davenport

Goldman School of Public Policy

School of Information

applied microeconomics, behavioral science, machine learning

Peter Bartlett

Dept of Statistics

Division of Computer Science (EECS)

machine learning, statistical learning theory, adaptive control

Pieter Abbeel

Division of Computer Science (EECS)

robotics, machine learning, artificial intelligence, Deep Learning

Hannah Zeavin

Dept of History

history of human sciences, history of technology and media, feminist science and technology studies, media theory

S. Katharine Hammond

School of Public Health

public health, environmental health sciences

Nika Haghtalab

Division of Computer Science (EECS)

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

David Bamman

School of Information

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

Michael Jordan

Dept of Statistics

Division of Computer Science (EECS)

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

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

Zachary Pardos

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

Kurt Keutzer

Division of Electrical Engineering (EECS)

computationally efficient machine learning and deep learning, AI

Nina Maggi Kelly

Dept of Environmental Science, Policy & Management

remote sensing, drones, ecosystem sciences, forests, geoinformatics, participatory web, GIS

Avideh Zakhor

Division of Electrical Engineering (EECS)

signal processing, image processing, computer vision, Deep Learning

Barry Shane

Dept of Nutritional Sciences & Toxicology

health and nutrition, nutritional sciences and toxicology, birth defects, nutritional genomics

Michel Maharbiz

Division of Electrical Engineering (EECS)

neural interfaces, bioMEMS, microsystems, MEMS, microsystems for the life sciences

Paolo D'Odorico

Dept of Environmental Science, Policy & Management

hydrology, ecohydrology, water resources, Water and Society, environmental sciences, Drylands, Desertification

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