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Hannes presented research recently published in Nature Computational Science on the directional, evolutionary optimization of transition metal complexes[1]. Using genetic algorithms, and extensive database of ligands as well as semi-empirical quantum chemistry calculations, chemical spaces containing up to a billion transition metal complexes could be efficiently explored. Furthermore, he discussed the possibility of generating ligands using a generative neural network architecture in order to use them as input for chemical space explorations with genetic algorithms.
The Artificial Intelligence in Chemistry Symposium is an annual conference organized by the Royal Society of Chemistry focused on the application of artificial intelligence (AI) techniques in the field of chemistry. This year’s edition, hosted at the Churchill College in Cambridge, featured a mixture of keynote talks, oral presentations, flash presentations, posters and opportunities for open debate, networking and discussion.
[1] Kneiding, Nova, Balcells, Nat. Comput. Sci., 2024, 4, 263.
Place of presentation: Cambridge, UK. September, 17 2024. Conference: https://www.rscbmcs.org/events/aichem7/
Funding: Hannes defended his PhD with the funding support of the COMPSCI MSCA program of the UiO..jpg)