Hannes Kneiding is a first year PhD Candidate at the Hylleraas Centre of Excellence, Department of Chemistry, UiO. He is also part of the CompSci doctoral program. His academic background is mostly computational physics with a focus on machine learning. At UiO, he is investigating predictive machine learning methods for specific classes of molecules based on data from quantum chemistry calculations.
At this seminar, Kneiding will introduce the general framework for graph learning in the context of quantum chemistry. He will discuss the data, representation and model aspects for the special case of transition metal complexes and close with some results on the tmQMg dataset.
→ Read more about the seminar series in the dScience website
Programme
11:30 – Doors open and lunch is served
12:00 – "Graph representation learning for transition metal complexes" by Hannes Kneiding (PhD Candidate, Hylleraas Centre)
This event is open for all PhD candidates and postdocs. No registration needed.