Seminar, TU Dortmund, 2026
Foundation models are pretrained once on broad and heterogeneous data distributions; however, real-world deployment typically requires reliable performance in narrow, specialized domains. This seminar will discuss fundamental and recent approaches to address the following question: How do we specialize foundation models to a target domain under computational and data constraints?
Seminar, TU Dortmund, 2025
Tabular data is everywhere and often at the core of data science tasks, from healthcare to e-commerce and the natural sciences. Yet it comes with unique challenges and research questions for machine learning:
Seminar, University of Tübingen, 2024
What is tabular data? And which model would you use for it? Why is tabular data challenging for machine learning? And how would you compare learning approaches on tabular data?
Seminar, University of Tübingen, 2024
Have you heard about AutoML? Do you wonder what LLMs can do for AutoML and vice versa? Then this seminar is for you!
Seminar, University of Tübingen, 2023
Have you ever trained an ML model and wondered how to efficiently optimize its hyperparameters? Then this seminar is for you!