While specific achievements are not listed, it mentions ongoing work focused on using machine learning to improve efficiency in quantum chemistry predictions.
Research Experience
Leads a team working on geometric machine learning in quantum chemistry, aiming to dramatically speed up quantum calculations using machine learning methods that respect the fundamental symmetries of the problem; involved in multiple research projects and closely collaborates with the university's excellence cluster, Ellis unit, and department.
Background
Focuses on developing principled AI methods to solve hard problems from the natural sciences. Specializes in fundamental algorithms and their application to complex problems with spatial structure.
Miscellany
Emphasizes the importance of team culture, advocating for being nice and doing great science. Located at IWR, Heidelberg University, which is an important place for interdisciplinary exchanges.