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. In SIAM J. Numer. Anal., 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.
See complete list of publications

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


  • Fast generation of random fields

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

  • Matlab $H^2$-matrix library

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