Scientific Computing and Numerical Analysis

Mathematics plays a central role in the design of efficient and reliable algorithms which, together with powerful high performance computers, are responsible for the success of the new approach to science and engineering through computational modeling and simulation.

Members of the research group in scientific computing/numerical analysis share a common interest in numerical methods for partial differential equations, one of the main modeling tools in science and engineering. Their research ranges from the design and analysis of numerical schemes to iterative methods for the discretized problems and their parallel implementations, with applications to mechanics (fluid and solid), electromagnetics, optimal design, image processing and digital geometry processing.

Faculty

Blaise Bourdin		Mathematics of materials science, scientific computing, optimal design
Susanne C. Brenner		Numerical analysis, finite element methods, multigrid methods, domain decompostion methods
Li-yeng Sung		Partial differential equations, inverse scattering, numerical analysis.
Shawn Walker		Finite element methods, free boundary problems, PDE-constrained (shape) optimization.
Xiaoliang Wan		Stochastic modeling, numerical methods for stochastic PDEs, minimum action method.
Hongchao Zhang		Nonlinear optimization and its applications, numerical analysis, numerical linear algebra.
Postdocs
Chris Davis		Numerical Analysis.
Duk-Soon Oh		Numerical Analysis.