Daniel Drzisga

Daniel Drzisga

SIMULIA R&D Software Engineer

Interests
  • Computational Fluid Dynamics
  • High-Performance Computing
  • Multigrid Methods
  • Matrix-free iterative solvers and preconditioners
  • Isogeometric Analysis
  • Multibody Simulation
Education

  • PhD in Applied Numerical Mathematics, 2020

    Technical University of Munich

  • MSc in Mathematics in Science and Engineering, 2015

    Technical University of Munich

  • BSc in Mathematics, 2013

    Technical University of Munich

Experience

 
 
 
 
 
SIMULIA R&D Software Engineer
Dassault Systèmes
Apr 2021 – Present Munich, Germany
SIMULIA R&D Simpack multibody simulation developer
 
 
 
 
 
Research associate
Technical University of Munich
Oct 2015 – Mar 2021 Garching, Germany
PhD student and postdoc in numerical mathematics
 
 
 
 
 
Intern
Lawrence Livermore National Laboratory
Aug 2019 – Nov 2019 Livermore, California
Internship on matrix-free preconditioners for MFEM

Recent Publications

A Matrix-Free ILU Realization Based on Surrogates
Matrix-free techniques play an increasingly important role in large-scale simulations. Schur complement techniques and massively …
Daniel Drzisga, Andreas Wagner, Barbara Wohlmuth
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Semi matrix-free twogrid shifted Laplacian preconditioner for the Helmholtz equation with near optimal shifts
Due to its significance in terms of wave phenomena a considerable effort has been put into the design of preconditioners for the …
Daniel Drzisga, Tobias Köppl, Barbara Wohlmuth
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The surrogate matrix methodology: Accelerating isogeometric analysis of waves
The surrogate matrix methodology delivers low-cost approximations of matrices (i.e., surrogate matrices) which are normally computed in …
Daniel Drzisga, Brendan Keith, Barbara Wohlmuth
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The surrogate matrix methodology: Accelerating isogeometric analysis of waves
Stencil scaling for vector-valued PDEs on hybrid grids with applications to generalized Newtonian fluids
Matrix-free finite element implementations for large applications provide an attractive alternative to standard sparse matrix data …
Daniel Drzisga, Ulrich Ruede, Barbara Wohlmuth
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The surrogate matrix methodology: A reference implementation for low-cost assembly in isogeometric analysis
A reference implementation of a new method in isogeometric analysis (IGA) is presented. It delivers low-cost variable-scale …
Daniel Drzisga, Brendan Keith, Barbara Wohlmuth
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