Research
The research focus for the Division of Numerical Analysis is on numerical methods for the solution of partial differential equations, stochastic differential equations and numerical linear algebra. This encompasses a wide range of methods, including finite difference, finite element and boundary integral methods, multi scale methods, Krylov methods and Monte Carlo methods. Applications are found within diverse fields such as for example electro magnetics, fluid mechanics, financial mathematics, quantum mechanics, biology and medicine.
Research Interests
Below follows a list of faculty members, and a few key words describing their research interests. For more information, please see their individual profile pages.
High frequency wave propagation, multiscale methods, uncertainty quantification, multiresolution analysis
Partial differential equations, mathematical physics, molecular dynamics, optimal control, stochastic differential equations, finite element methods.
Boundary integral methods, fast summation methods, quadrature, multiphase flow with drops and particles.
Analysis and numerical methods for differential-algebraic equations, Computational Systems Biology, Computational Neuroscience, ill-posed problems, multiscale systems.
Computational Quantum Physics, Error Estimation, Finite Elements, Multiscale Methods
Numerical linear algebra, iterative algorithms, large-scale systems, eigenvalue problems, Krylov methods, computational systems and control, high performance computing
Optimal Control Theory, Ab Initio Molecular Dynamics, Stochastic Modeling.
Finite element methods, Partial differential equations, Multiphase flow.
