The Department of Applied Mathematics and Statistics provides a unified home for the mathematical sciences. It is now the only such comprehensive mathematical sciences department among U.S. universities. It has 20 full-time faculties plus 15 adjunct faculties with primary appointments in other Stony Brook departments or in federal and industrial research laboratories.
Education: It has over 220 graduate students studying at the M.S. and Ph.D. levels in tracks in:
- computational applied mathematics
- computational biology
- operations research/quantitative finance
It awards about 20 Ph.D.’s and 55 M.S.’s a year.
The department also has an extremely successful undergraduate major, graduating about 110 B.S.’s a year, close to 5% of all Stony Brook B.S.’s. For decades, Stony Brook has graduated a higher percentage of Bachelor’s degrees in mathematics—mostly in Applied Math-- than any other U.S. public university.
Research: Applied Mathematics and Statistics faculty work on a wide range of important problems, from designing better drugs to fight AIDS to assessing the effectiveness of foster care programs to helping the FAA route airplanes around weather systems to designing fusion reactors. An underlying premise of all research is that problems drive the mathematics, as opposed to having theories in search of applications. Almost all research projects involve collaborations with faculty in other disciplines. All faculty has external funding for their studies, averaging $150,000 a year per professor.
With the recent endowed gift of the Frey Family Chair in Quantitative Finance, the department is expanding its research and doctoral training in this area.
- Biostatistics, bioinformatics, brain image analysis
- Statistical genetic epidemiology applied longitudinal data analysis
- Financial econometrics, macro-econometrics
Computational Applied Mathematics (CAM):
- Computational science, computational physics, computational medicine
- Supercomputing, finite-element methods, multigrid solvers, front tracking
- Computational fluid dynamics, turbulence, porous media
- Empirical finance, financial econometrics, market and credit risk management
- Asset-liability modeling, high-frequency analysis, risk analysis and optimization
- Computational geometry
- Optimization, smart grids, energy management, transportation systems
- Analysis, optimization, and control of stochastic and deterministic systems
- Computational glycobiology; biochemical network modeling
- Drug design targeting AIDS, breast cancer, botulism, pain
- Protein design, structure prediction; ligand docking
- Computational immunology, evolutionary systems biology
Program taught in: