During his PhD studies, Mads Greisen Højlund developed computational methods for simulating the motion of molecules, e.g. chemical reactions. This task involves two main challenges, both of which were addressed in the thesis: (i) Constructing the so-called potential energy surface (PES) and (ii) solving the Schrödinger equation defined by the PES. Mads Greisen Højlund developed a novel machine learning approach for speeding up PES construction and introduced a new wave function method for solving the Schrödinger equation. 

The research findings pave the way for more accurate simulations of chemical processes. Furthermore, the new machine learning method is not limited to PES construction and can be used by the broader scientific community.

The PhD study was completed at the Department of Chemistry, Faculty of Natural Sciences, Aarhus University.

This summary was prepared by the PhD student.

Time: Friday, 19 June 2026 at 13.00.
Place: Building 1514, Room 213, Auditorium I, Department of Chemistry, Aarhus University, Langelandsgade 140, DK-8000 Aarhus C.
Title of PhD thesis: Dynamic Basis Function in Coupled Cluster Theory & Scalable Gaussian Process Regression on High-Dimensional Incomplete Grids
Contact information: Mads Greisen Højlund, e-mail: madsgh@chem.au.dk, tel.: +45 20 91 00 52.
Members of the assessment committee:
Professor Tucker Carrington Jr, Department of Chemistry, Queen’s University, Canada.
Professor Jacob Kongsted, Department of Physics, Chemistry and Pharmacy, University of Southern Denmark, Denmark.
Professor Henrik Stapelfeldt (chair), Department of Chemistry, Aarhus University, Denmark.
Main supervisor: Professor Ove Christiansen, Department of Chemistry, Aarhus University, Denmark.
Language: The PhD dissertation will be defended in English.

The defence is public.
The PhD thesis is available for reading at the Graduate School of Natural Sciences/GSNS, Ny Munkegade 120, building 1521, 8000 Aarhus C