## Recent Publications

1. Feischl, M. Optimal adaptivity for a standard finite element method for the Stokes problem. Preprint: arXiv:1710.08289: To appear in SIAM J. Numer. Anal., 2019.
2. Dick, J.; Feischl, M. and Schwab, C. Improved Efficiency of a Multi-Index FEM for Computational Uncertainty Quantification. , to appear, 2019.
3. Akrivis, G.; Feischl, M.; Kovács, B. and Lubich, C. Higher-order linearly implicit time discretization of the Landau--Lifshitz--Gilbert equation. Preprint: arXiv:1903.05415, 2019.

## Research interests

My research focuses on three main areas:

• Partial differential equations with random coefficients and fast random field generation
• Computational micromagnetism and numericas and theory of the Landau-Lifshitz-Gilbert equation
• Optimal adaptive mesh refinement and a posteriori error estimators

## Software

• This Matlab program uses $H^2$-matrices to efficiently evaluate Gaussian random fields on arbitrary pointsets.

• This is a simple, and very limited implementation of the $H^2$-matrix approach in Matlab.