Niklas Kemper

Niklas Kemper is a researcher at the Technical University of Munich (TUM), affiliated with the TUM School of Computation, Information and Technology and the Department of Computer Science. He focuses on robust machine learning, graph neural networks, and temporal data analysis. His work intersects Bayesian deep learning and efficient machine learning algorithms.

• Education: M.Sc. in Computer Science (2021–2024) and B.Sc. in Computer Science (2017–2021) from TUM, plus a Philosophicum (2020–2023) from the Munich School for Philosophy.

Research Interests include molecular graph neural networks, fragment bias analysis, and scalable learning methods. His recent work at ICML 2024 explores expressivity and generalization in molecular GNNs. He has been recognized with scholarships from the German Academic Scholarship Foundation and Bavaria’s Max Weber Program.