Stefan Hegselmann
Researcher at BIH and resident physician at Charité in Berlin.

I am interested in machine learning for healthcare. My research focuses on using large generative models to enable efficient, high-performing predictions, and on applying natural language processing techniques to clinical text. I am particularly interested in using state-of-the-art machine learning methods to address meaningful medical problems and improve healthcare delivery.
I am currently an affiliated postdoctoral researcher at the Eils lab focussing on artificial intelligence in healthcare. I am also a resident physician at the Department of Cardiology, Angiology and Intensive Care Medicine at the Charité in Berlin, where I am involved in clinical practice. My goal is to bridge the gap between modern machine learning and clinical practice.
Previously, I have obtained a Master’s degree in computer science from RWTH Aachen University with stays at the University of Gothenburg and UC Berkeley. After that I obtained a medical degree (MD) and a PhD in computer science from the University of Münster and worked with the Clinical ML group at MIT.
You can find all my papers on my Google Scholar profile.
news
Apr 01, 2025 | Transferred to this new website. |
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selected publications
- Tabllm: Few-shot classification of tabular data with large language modelsIn International Conference on Artificial Intelligence and Statistics, Dec 2023
- A data-centric approach to generate faithful and high quality patient summaries with large language modelsConference on Health, Inference, and Learning 2024, Dec 2024