List of Faculty in the Graduate Group in Applied Mathematics (GGAM)

GGAM comprises faculty members from departments across the campus, including its home, the Department of Mathematics. Below is a brief description of faculty research, links to personal and departmental web pages plus some "Related Courses" which can serve as a general study guideline for students interested in research with a particular faculty member. Students who want a more complete description of a faculty member's research interests are encouraged to contact them.

Choose a department below or list all faculty
Biomedical Engineering Biostatistics, Public Health Sciences
Bodega Marine Laboratory Center for Neuroscience
Chemical Engineering Chemical Engineering and Materials Science
Civil and Environmental Engineering Computer Science
Department of Pharmacology Economics
Electrical and Computer Engineering Environmental Science and Policy
Evolution and Ecology Graduate School of Management
Land, Air and Water Resources Materials Science & Engineering
Mathematics Mechanical and Aeronautical Engineering
Mechanical and Aerospace Engineering Microbiology and Molecular Genetics
Molecular and Cellular Biology Neurobiology, Physiology and Behavior
Physics Statistics

NameResearch/Related Courses
Aue, AlexanderTime series analysis, structural break analysis, theoretical/mathematical questions arising in fields of application, such as economics, finance and environmental science.
[Related Courses]
Balasubramanian, KrishnakumarInferential and computational issues in non-parametric statistics, high-dimensional statistics, network analysis and stochastic optimization.
[Related Courses]
Ding, XiucaiMy current research focuses on the following areas: 1. Statistical and algorithmic applications of random matrix theory, spin glass theory and integrability theory; 2. Mathematical and statistical foundation for manifold learning and machine learning; 3. Non-stationary time series analysis and functional time series analysis.
[Related Courses]
Karzand, MinaTheoretical Machine Learning and Applied Probability: Sequential Learning, Graphical Models, Optimization Theory.
[Related Courses]
Li, XiaodongMethods and theory in high-dimensional statistics, robust statistical learning, network data analysis, and signal processing.
[Related Courses]
Lopes, MilesMy main research areas are in high-dimensional statistics and machine learning, with a particular focus on bootstrap methods and randomized numerical linear algebra.
[Related Courses]
Mueller, Hans-GeorgFunctional Data Analysis, Semiparametric Modelling, Applications in Biodemography, Genetics, Medicine, e-Commerce and Finance.
[Related Courses]
Wang, Jane-LingDimension reduction methods; functional data analysis; longitudinal data analysis; nonparametric functional estimation; aging research; survival analysis.
[Related Courses]