Group Leader, Reliable AI, Helmholtz AI
Dr. Prof. Niki Kilbertus
“We are developing the foundations of AI to propel scientific progress.”
Academic Career and Research Areas
Prof. Dr. Niki Kilbertus grew up in Austria, studied Physics and Mathematics in Regensburg, and spent time at Harvard and Stanford during his studies. He obtained his PhD in the Cambridge-Tübingen program as an ELLIS student. During his PhD, he interned at Deepmind, Google, and Amazon, before joining Helmholtz AI as Young Investigator Group leader and the Technical University of Munich as professor working on mechanistic ML, dynamical systems, causality, and more broadly AI for science.
His ERC Starting Grant project DYNAMICAUS (2025) combines machine learning with causal inference for complex dynamical systems, with applications in climate science, healthcare, and epidemic preparedness. He is also a co-PI in the BMBF-funded CausalNet project alongside Stefan Bauer and partners from LMU, TUM, and KIT. Niki was recognised as AI Newcomer of the Year by the Federal Ministry of Education and Research and the German Informatics Society in 2019, and received the Leopoldina Prize for Young Scientists in 2024 for his achievements in ethical machine learning.
Fields of Work and Expertise
AI for Science
Dynamical Systems
Causality
Professional Background
B.Sc. and M.Sc. in Mathematics and Physics, University of Regensburg (incl. research stays at Harvard 2014 and Stanford 2015–2016)
PhD, University of Cambridge (Cambridge–Tübingen PhD Fellowship in Machine Learning; advisor: Bernhard Schölkopf, MPI Tübingen)
AI Newcomer of the Year, Federal Ministry of Education and Research (BMBF) and German Informatics Society (GI)
Research Group Leader, Helmholtz AI at Helmholtz Munich
Professor for Ethics in Systems Design and Machine Learning, TU Munich
Honors and Awards
AI Newcomer of the Year (2019) – Federal Ministry of Education and Research (BMBF) and German Informatics Society (GI);
Cambridge–Tübingen PhD Fellowship in Machine Learning (2016–2020) – highly competitive joint fellowship for doctoral research at Cambridge and MPI Tübingen;
Leopoldina Prize for Young Scientists (2024) – German National Academy of Sciences Leopoldina, for outstanding achievements in ethical machine learning;
ERC Starting Grant (2025) – European Research Council, for the project DYNAMICAUS: causal analysis in complex dynamical systems.
