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.

News

• 9th Nov’23 · 🗨️ Together with Marius Lindauer I gave a talk at MLOps’23: “Hyperparameter Optimieren mit AutoML”
• Sept’23 · 📓 I offer a seminar on “Automated Machine Learning and Hyperparameter Optimization” in the winter semester. Find more details here
• Sept’23 · 🥳 I am thrilled to be one of three program chairs at next year’s AutoML Conf in Paris
• 12th-15th Sept’23 · 🥳 Together with Matthias Feurer I am organizing the social program for the AutoML Conference! All important details can be found on automl.cc
• July’23 · 🗨️ Together with Marius Lindauer I will give a lecture on “AutoML: Accelerating Research on and Development of AI Applications” at the ESSAI Summer School!
• June’23 · 🗨️ Together with Eddie Bergman I gave a Hands-On Session at the nextgen_AI Freiburg workshop: “Automated Machine Learning with Auto-sklearn”
• Jan’23 · 📝 Our paper Mind the Gap: Measuring Generalization Performance Across Multiple Objectives got accepted at IDA 2023.
• Jan’23 · 📝 Our paper TabPFN: A Transformer That Solves Small Tabular Classification Problems in a Second got accepted to ICLR 2023.
• Jan’23 · 🥳 I am very excited to start a new position as an early career group leader for AutoML for Science in the Cluster of Excellence “ML in Science” at the University of Tübingen!

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!