Mathematics in Computational Sciences

Mathematics in Computational Sciences

Mathematics in Computational Sciences

All information about the groups of Mathematics in Computational Science and Engineering can be found in the webpage MATHICSE-Group


Numerical linear algebra and high-performance computing, low-rank matrix and tensor techniques, computational differential geometry, eigenvalue problems, high-performance computing, and model reduction.

Chair of Computational Mathematics and Numerical Analysis (ANMC)

Assyr Abdulle

Numerical analysis and computational mathematics, modeling and numerical analysis of multiscale partial differential equations, numerical methods for atomistic simulation, numerical methods for stiff and stochastic differential equations.

Development of reliable numerical simulations of complex models appearing in physics, engineering and life science applications, such as fluid-structure interaction in hemodynamics, heart electromechanics, flows in porous media, etc.

Deparis Group
Numerical Analysis of PDEs, parallel computing, reduced order modeling. Applications to the simulaiton of the Cardio-vascular system.

Picasso Group (GR-PI) (former Chair of Numerical Analysis and Simulation ASN)
Numerical solution of partial differential equations.

My general research interests concern nonlinear mechanics and mathematics, with emphases on i) parameter continuation, bifurcation and stability exchange results, ii) variational principles.

High-order and spectral methods for PDEs, Numerical analysis for time-dependent PDEs, Reduced order methods, Computational wave problems, Machine learning in scientific applications, High performance and parallel computing, Computational science and engineering.

Design and analysis of numerical algorithms for partial differential equations, numerical methods for problems with discrete mathematical structure, numerical techniques to improve the integration between numerical simulation and geometric modelling, applications from elasticity to electromagnetism.

Theory and applications of optimization in continuous variables, with a focus on geometry and non-convexity; aspects of numerical analysis and statistical estimation through the lens of optimization and geometry.