Short Bio. I am an associate professor for ML and AI at the Lamarr Institute and TU Dortmund. Before that I was an early Career Research Group Leader AutoML for Science in the Cluster of Excellence Machine Learning for Science at the University of Tübingen (2023-2025). I received my PhD the University of Freiburg, under the supervision of Frank Hutter and Marius Lindauer as part of the ML Lab (2022). I co-developed several open-source tools for HPO methods and AutoML systems and have been a member of the team winning three AutoML competitions (2016, 2018, 2020). I am a junior head of the Automl.org group, member of COSEAL and ELLIS, and a faculty member of IMPRS-IS. Furthermore, I co-organized the AutoML workshop series at ICML in 2019, 2020 and 2021, served as a social chair (2022,2023), a program chair (2024) and a non-traditional content track chair (2025) for the AutoML Conference and am part of Tübingen Women in Machine Learning.

Research Interests. I research methods for automated machine learning (AutoML), with a focus on AutoML Systems and Hyperparameter optimization. In this context, I aim to better understand and apply foundation models for Tabular Machine Learning. Motivated by the goal provide easy access to state-of-the-art ML, I research how to improve and extend both, AutoML methods and ML models, to leverage the full potential of ML for new applications in science. Specifically, I aim to understand how to best develop AutoML methods to automatically design, select and fit the best ML solution for a given task.

News

• Oct'25 · 📓 I offer my first seminar at TU Dortmund on "Tabular Machine Learning". See here.
• Oct'25 · 📝 Our paper Put CASH on Bandits: A Max K-Armed Problem for Automated Machine Learning" got accepted at NeurIPS'25. We will present this work in San Diego and Kopenhagen.
• Oct'25 · 🥳 Excited to join TU Dortmund University and the Lamarr Institute as a professor for ML and AI. I'll also extend my lab, see here.
• July'25 · 📝 Our paper "In-Context Decision Making for Optimizing Complex AutoML Pipelines" got accepted at ECAI'25. We will present this work also at EWRL'25. See you in Bologna and Tübingen!
• June'25 · 📝 Our paper "In-Context Learning of Soft Nearest Neighbor Classifiers for Intelligible Tabular Machine Learning" got accepted as a poster (and oral) at TRL@ACL'25. See you in Vienna!
• June'25 · 🙏 The 5th AutoML School is over. Thanks to all participants and speakers for this fantastic event and see you next year in Dortmund! Videos can be found here.
• June'23 · 📣 I co-chair the non-archival content track for AutoML 2025 in New-York (together with Nick Erickson. We're looking forward to your (creative) submissions. Deadline Aug 4th.

• Jan'23 · 🥳 I am very excited to start my own Early Career Research Group for AutoML for Science at the Cluster of Excellence "ML for Science" at the University of Tübingen!

Misc

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

Want to work with me? See this call for multiple PhD positions for our new lab in Dortmund or reach out to me in case of any questions!