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
Bai, ZhaojunNumerical linear algebra (theory, algorithm development & analysis)
D'Souza, RaissaNetwork theory, statistical physics, computational science, probability, applied math, cellular automata, and networking protocols.
Doty, DavidMolecular computing, self-assembly, chemical reaction networks, distributed computing, theory of computing, algorithmic information theory, probability
[Related Courses]
Gygi, FrançoisNumerical methods of quantum mechanics; Large-scale parallel computing; Molecular dynamics.
[Related Courses]
Koehl, PatriceMy research program focus on understanding protein structures. I am interested in characterizing their shapes using mathematical and computational approaches, and to use this information to improve our understanding of their stability. I am also interested in characterizing the subset of sequence space compatible with a protein structure: this is an indirect approach to understanding protein sequence evolution. In parallel, I am involved in the development of new algorithms for predicting the structure of a protein, based on its sequence. My department web pages are: http://www.cs.ucdavis.edu/people/faculty/koehl.html in CS and http://genomecenter.ucdavis.edu/koehl_cv.html at the Genome Center.
Liu, XinNetwork resource management, optimization, machine learning.
[Related Courses]
Mitrovic, SlobodanTheoretical computer science
[Related Courses]
Sonnewald, MaikeGeophysical fluid dynamics; dynamical systems; ocean science; climate science.
[Related Courses]