Administrative data

Michael Herbst

michael.herbst@epfl.ch +41 21 693 89 89 https://matmat.org

EPFL SB MATH MATMAT1
MA B1 467 (Bâtiment MA)
Station 8
1015 Lausanne

+41 21 693 89 89
Office: MA B1 467
EPFL › SB › MATH › MATMAT1

Website: https://matmat.org/

+41 21 693 89 89
EPFL › STI › IMX › MATMAT2

Website: https://matmat.org/

+41 21 693 89 89
EPFL › SB › SB-SMA › SMA-ENS

Website: https://sma.epfl.ch/

Expertise

For more information about our research, see https://matmat.org/research/.

Publications Teaching & PhD

MatMat group publications

Journal Articles

2025

Algorithmic differentiation for plane-wave DFT: materials design, error control and learning model parameters

N. F. Schmitz; B. Ploumhans; M. F. Herbst

npj Computational Materials. 2025. DOI : 10.1038/s41524-025-01880-3.

Detailed record

View at publisher

Mathematical Methods in Quantum Chemistry

G. Dusson; M. F. Herbst; B. Stamm

Oberwolfach Reports. 2025. DOI : 10.4171/owr/2025/15.

Detailed record

View at publisher

Kohn-Sham inversion with mathematical guarantees

M. F. Herbst; V. H. Bakkestuen; A. Laestadius

Physical Review B. 2025. DOI : 10.1103/physrevb.111.205143.

Detailed record

View at publisher

2024

Multitask methods for predicting molecular properties from heterogeneous data

K. E. Fisher; M. F. Herbst; Y. M. Marzouk

The Journal of chemical physics. 2024. DOI : 10.1063/5.0201681.

Detailed record

View at publisher

ddX: Polarizable continuum solvation from small molecules to proteins

M. Nottoli; M. F. Herbst; A. Mikhalev; A. Jha; F. Lipparini et al.

Wiley Interdisciplinary Reviews: Computational Molecular Science. 2024. DOI : 10.1002/wcms.1726.

Detailed record

View at publisher

2023

Reduced basis surrogates for quantum spin systems based on tensor networks

P. Brehmer; M. F. Herbst; S. Wessel; M. Rizzi; B. Stamm

Physical Review E. 2023. DOI : 10.1103/PhysRevE.108.025306.

Detailed record

View at publisher

Teaching & PhD

PhD Students

Niklas Frederik Schmitz, Anna Paulish, Bruno Ploumhans

Courses

Error control in scientific modelling

MATH-500

Errors are ubiquitous in computational science as neither models nor numerical techniques are perfect. With respect to eigenvalue problems motivated from materials science and atomistic modelling we discuss, implement and apply numerical techniques for estimating simulation error.

Numerical analysis

MATH-251(b)

The students will learn key numerical techniques for solving standard mathematical problems in science and engineering. The underlying mathematical theory and properties are discussed.