Find UC Berkeley Faculty

Research Expertise and Interest

Use quotes to search for an exact phrase. Example: "computational biology"

Name

Department

Sophia Rabe-Hesketh

Sophia Rabe-Hesketh

School of Education

biostatistics, educational statistics, latent variable models, missing data methods, multilevel models, generalized linear latent and mixed models, hierarchical models, longitudinal data, Item response models, structural equation models

Haas School of Business

labor markets, human resources, data analysis and statistical methods

Peng Ding

Dept of Statistics

Statistical causal inference, missing data, Bayesian statistics, applied statistics

Dept of Statistics

data science, Educational Data Science, scientific computing

Patrick Bradshaw

Patrick Bradshaw

School of Public Health

epidemiologic methods, Bayesian methods, cancer epidemiology, cardiometabolic risk

Elizabeth Purdom

Elizabeth Purdom

Dept of Statistics

computational biology, bioinformatics, statistics, data analysis, sequencing, cancer genomics

Bin Yu

Dept of Statistics

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

Song Mei

Dept of Statistics

data science, statistics, machine learning

Michelle Wilkerson

Michelle Wilkerson

School of Education

K-12 math and science education, science education, mathematics education, computing education, design-based research, computers in K-12 education, data literacy, data science education

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Division of Computer Science (EECS)

data science, machine learning, inequality, Healthcare

Photo of Abhishek Nagaraj in outside setting.

Abhishek Nagaraj

Haas School of Business

innovation, entrepreneurship, big data, cartography

Mark van der Laan

Dept of Statistics

School of Public Health

targeted learning, real-world data integration in RCTs, sequential adaptive designs, computational biology and genomics, censored data and survival analysis, medical research, inference in longitudinal studies

Xiudi Li

School of Public Health

causal inference, data integration, federated learning and transfer learning, electronic health records, clinical trials, High Dimensional Data Analysis

Ali Kakhbod

Haas School of Business

financial economics, liquidity, market microstructure, big data, contracts

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

Xin Guo

Dept of Industrial Engineering & Operations Research

stochastic control and games, theory of machine learning and applications to medical and financial data analysis, applied probability and stochastic models

Dept of Political Science

causal inference, survey data analysis

Alice M. Agogino

Alice M. Agogino

Dept of Mechanical Engineering

intelligent learning systems, information retrieval and data mining, multiobjective and strategic product design, nonlinear optimization, probabilistic modeling, intelligent control and manufacturing, sensor validation and fusion and diagnostics, wireless sensor networks, multimedia and computer-aided design, design databases, design theory and methods, MEMS Synthesis and CAD, artificial intelligence and decision and expert systems, gender equity

Jennifer Anne LaFleur

School of Journalism

Data journalism, investigative journalism, disability, inequality, criminal justice

Paul Grigas

Dept of Industrial Engineering & Operations Research

optimization, machine learning, data-driven decision-making

Dept of Statistics

applied statistics, functional genomics, translational bioinformatics, high dimensional and integrative genomic/genetic data analysis, network modeling, hierarchical multi-lable classification

William Lester, Jr.

William A. Lester, Jr.

Dept of Chemistry

theoretical and physical chemistry, advances in basic theory, computational methods, study of molecular electronic structure, quantum Monte Carlo method, Born-Oppenheimer approximation

Division of Computer Science (EECS)

machine learning, data science, artificial intelligence

David Holtz

Haas School of Business

online marketplaces and platforms, computational social science, data science, experimental economics

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