Applied mathematics, numerical analysis and scientific computing
The Seminar for Applied Mathematics (SAM) is committed to conducting fundamental research in the mathematical analysis of continuum modals arising in the sciences and engineering, in their accurate discretization and efficient solution, including the development of related algorithms and software for high-performance computing.
Research at SAM combines rigorous mathematical analysis and algorithmic developments inspired and driven by concrete applications. It encompasses the derivations and analysis of mathematical models, investigations of stability, convergence, and structure of discretizations, and considerations on complexity and efficient implementation of numerical methods, including those on massively parallel, high-performance computing platforms.
Focus on applications at SAM involves a keen interest in interdisciplinary research, which is reflected in the numerous collaborations with scientists outside mathematics and joint projects with the industry.
Rima Alaifari
Research interests: nverse problems and regularization, medical imaging, applied harmonic analysis, multiresolution analysis, signal processing
Habib Ammari
Research interests: physical applied mathematics, inverse problems and imaging, wave propagation in complex media, multi-scale analysis, biomedical modelling
Vasile Gradinaru
Research interests: engineering mathematics, computational electromagnetics, computational physics, computational chemistry, finite element methods, interpolation and approximation, numerical methods for ODEs, multi-scale methods
Ralf Hiptmair
Research interests: computational electromagnetics and wave propagation, numerical shape calculus and shape optimiziation, boundary element and finite element methods, structure preserving discretization of PDEs and fast iterative solvers
Roger Käppeli
Research interests: computational astrophysics, computational hydrodynamics and magnetohydrodynamics, numerical methods for hyperbolic conservation laws and high performance computing
Siddhartha Mishra
Research interests: hyperbolic conservation laws: theory and numerical methods, computational fluid dynamics, computational astrophysics, high-performance computing, modeling and computation of complex systems, scientific machine learning
Christoph Schwab
Research interests: numerical analysis and scientific computing, space-time compressive discretizations of evolution equations, PDEs with random input data, high-dimensional numerics for PDEs with multiple scales, sparse tensor approximations of high-dimensional and stochastic PDEs, multilevel Monte Carlo and Quasi-Monte Carlo algorithms for PDEs, deep neural network approximation