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

• Feb'26 · 📓 I will offer a seminar on Adapting and Fine-Tuning Foundation Models.
• Dec'25 · 👋 Meet us at NeurIPS, EurIPS and the ELLIS Unconference: Put CASH on Bandits: A Max K-Armed Problem for Automated Machine Learning at NeurIPs, "AutoML for Simulation-based Inference" at Amortized ProbML, "TabPFN-Wide: Continued Pre-Training for Extreme Feature Counts" at AI for Tabular Data and "Towards Understanding Layer Contributions in Tabular In-Context Learning Models" at AI for Tabular Data.
• 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'25 · 📣 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? There are currently no open positions.