Publications
You can also find my publications on my Google Scholar and ORCID profiles. A detailed list of citable code packages accompaning my publications can be found at the end of my Software page.
Submitted Articles
Journal Articles
M. S. Ackermann, L. Balicki, S. Gugercin, and S. W. R. Werner. The NLAAA algorithm for rational approximation – applications to model order reduction. Research in the Mathematical Sciences, 13(4):82, 2026. doi:10.1007/s40687-026-00668-1

M. S. Ackermann, S. W. R. Werner, I. V. Gosea, and S. Gugercin. Second-order AAA algorithms for structured data-driven modeling. Advances in Computational Mathematics, 52(5):76, 2026 doi:10.1007/s10444-026-10347-y

M. S. Ackermann, S. Reiter, and L. N. Trefethen. L2 and L∞ rational approximation on the unit disk. Research in the Mathematical Sciences, 13(3), 2026. doi:10.1007/s40687-026-00650-x
M. S. Ackermann and S. Gugercin. Time-domain iterative rational Krylov method. SIAM Journal on Scientific Computing, 47(3):A1628–A1651, 2025. doi:10.1137/24M1678167
M. S. Ackermann and S. Gugercin. Frequency-based reduced models from purely time-domain data via data informativity. SIAM Journal on Scientific Computing, 47(2):A1225–A1250, 2025. doi:10.1137/23M1624130
Proceedings
- M. S. Ackermann, P. Bochev, and D. Ridzal. Towards a reduced model for hyperbolic partial differential equations. Technical report SAND2025-14267O, The Computer Science Research Institute at Sandia National Laboratories, Albuquerque, New Mexico, pages 3–16, 2025.

Software
M. S. Ackermann and S. W. R. Werner. Code, data and results for numerical experiments in “Second-order AAA algorithms for structured data-driven modeling” (version 1.1), May 2026. doi:10.5281/zenodo.19895043
S. Reiter, M. S. Ackermann and L. N. Trefethen. Code and Results for Numerical Experiments in “L2 and L∞ rational approximation on the unit disk” (version 1.0), February 2026. doi:10.5281/zenodo.18746402
M. S. Ackermann, S. W. R. Werner, and L. Balicki. Code, data and results for numerical experiments in “A refined nonlinear least-squares method for the rational approximation problem”, January 2026. doi:10.5281/zenodo.18317028
M. S. Ackermann. Code and Data for the Numerical Experiments in “Time-Domain Iterative Rational Krylov Method”, July 2024. doi:10.5281/zenodo.12751391
M. S. Ackermann. Code and Data for the numerical experiments in “Frequency-Based Reduced Models from Purely Time-Domain Data via Data Informativity” (version 1.0), November 2023. doi:10.5281/zenodo.10076325
Theses
- M. S. Ackermann. Frequency-domain learning of dynamical systems from time-domain data. Thesis, Virginia Tech, 92 pages, June 2022.

