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Can we teach a computer how to optimize molecules and materials?

PhD defense, Friday 15th of October. Søren Meldgaard.

2021.10.15 | Karen Konradi

Søren Meldgaard

During his PhD studies, Søren Meldgaard researched how atoms arrange themselves at the atomic level. By solving a complex optimization problem requiring heavy computational calculations the solution can be found. Søren Meldgaard has introduced machine learning algorithms to reduce to amount of calculations required, thereby facilitating a study of more complex systems.


The new research findings contribute to better understand how atoms come together to form molecules and materials. Furthermore, it is demonstrated how machine learning can contribute to solving physics problems.

The PhD study was completed at Institute of Physics and Astronomy, Faculty of Natural Sciences, Aarhus University.

This summary was prepared by the PhD student.

Time: Friday, 15th of October at 14.15
Place: Building 1525 room 626, Department of Physics and Astronomy, Aarhus University, Ny Munkegade 120, 8000 Aarhus
Title of PhD thesis: Machine learning guided atomistic structure optimization

Contact information: Søren Meldgaard, e-mail: sm@phys.au.dk

Members of the assessment committee:

Professor Heather J. Kulik, Chemical Engineering, Massachusetts Institute of Technology (MIT), USA

Professor Matthias Rupp, Computer Science, Universität Konstanz, Germany

Professor Karsten Riisager (chairman), Department of Physics and Astronomy, Aarhus University, Denmark

Main supervisor:
Professor Bjørk Hammer, Department of Physics and Astronomy, Aarhus University, Denmark

Language: The PhD dissertation will be defended in English

The defense is public.
The PhD thesis is available for reading at the Graduate School of Natural Sciences/GSNS,

Katrinebjergvej 89F, building 5132, 8200 Aarhus N.

PhD defence
16882 / i43