CV

Dr. Michael Reichelt · Applied mathematics, numerical PDEs, and scientific computing

Current Position

Postdoctoral Researcher, Helmut-Schmidt University / University of the Federal Armed Forces Hamburg, since April 2026.

Research Profile

My work focuses on numerical methods for partial differential equations, especially space-time finite element methods, structure-preserving discretizations, Maxwell’s equations, geometric calculus, fast solvers, and high-performance scientific computing.

Academic Background

  • PhD in Mathematics, Graz University of Technology, 2026, with distinction. Thesis defended on February 25, 2026. Dissertation: Space-time finite element methods and fast solvers for parabolic problems. Supervisor: Prof. Olaf Steinbach.
  • MSc in Technical Physics, Graz University of Technology / University of Graz, 2023, with distinction.
  • MSc in Mathematics, Graz University of Technology / University of Graz, 2022.
  • BSc in Mathematics, Graz University of Technology / University of Graz, 2019.
  • BSc in Technical Physics, Graz University of Technology, 2017.

Selected Experience

  • University Project Assistant, Graz University of Technology, 2022-2026. Research on space-time finite element methods, operator preconditioning, FFT-based acceleration, and HPC implementation in C++ and Python.
  • Developer, AVL List, 2015-2022. Development and maintenance of C++ and Fortran solvers for multi-body and vehicle dynamics simulation tools, including numerical linear algebra and performance-oriented implementation.
  • Teaching Assistant, Graz University of Technology, 2017-2021. Teaching support for undergraduate mathematics courses, exercise sessions, grading, and exams.

Research Stay

Visiting PhD Researcher, TU Darmstadt, Institute for Accelerator Science and Electromagnetic Fields, 2024. Research stay in the framework of TRR361/F90 CREATOR with Prof. Sebastian Schöps.

Collaborative Projects

TRR361/F90 CREATOR — Computational Electric Machine Laboratory, 2022-2026. Doctoral researcher with focus on space-time finite element methods for electric machines.

Scientific Computing

Programming and numerical software experience includes C++, Python, Fortran, Rust, PETSc, MFEM, NGSolve, finite element implementation, solver development, and high-performance computing workflows.

Talks and Publications

Selected conference contributions and publications are maintained separately on the talks and publications pages.