About me

I am an Early Career Research Group Leader AutoML for Science in the Cluster of Excellence Machine Learning for Science at the University of Tübingen.

Short Bio

Her research focuses on methods for automated machine learning (AutoML), hyperparameter optimization (HPO), and efficient benchmarking. Motivated by the goal of further democratizing the application of machine learning for scientific researchers and practitioners, she researches how to improve and extend AutoML systems to leverage the full potential of ML for new applications.

Previously, she was part of the ML Lab at the University of Freiburg, where she completed her Ph.D. under the supervision of Frank Hutter and Marius Lindauer (2022). Katharina also co-developed open-source tools for HPO methods and AutoML systems and has been a member of the team winning three AutoML competitions (2016, 2018, 2020). She is part of the Automl.org group, co-organized the AutoML workshop series at ICML in 2019, 2020 and 2021 and serves as a social chair (2022,2023) and as a program chair (2024) for the AutoML Conference.


Note: For links to slides, tutorials and videos, please see talks, teaching and Automl.org

Want to work with me? I typically recruit PhD students via the IMPRS-IS graduate school (Deadline 15th November). Here is an example call for a PhD position or reach out to me for more details!