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Welcome to the Lucerne Medical AI Lab

Building safe and trustworthy AI for healthcare

We are a research group working on machine learning for healthcare, with the goal of enabling safer and more reliable clinical decision-making. Our work focuses on developing interpretable and uncertainty-aware learning methods that are robust to heterogeneous data and capable of generalizing across tasks and settings. Our research is informed by close collaboration with clinicians and domain experts to ensure that our methodological advances can ultimately translate into real clinical workflows.

Latest news

Jan Nikolas Morshuis defended his PhD

Nikolas Morshuis successfully defended his PhD thesis on robustness and inherent ambiguity in accelerated MRI reconstruction.

Jun 2026

SAIMI 2026 in Bern

Susu Sun, Anna Wundram and Paul Fischer presented their research at the Symposium on Artificial Intelligence in Medical Imaging in Bern.

Jun 2026

Universal Algorithm-Implicit Learning accepted at ICML 2026

Stefano Woerner’s final PhD paper, introducing the TAIL meta-learner, was accepted at ICML 2026.

Apr 2026

SEG4SEG accepted as a MIDL 2026 spotlight

Our paper on discovering systematically underperforming subgroups in medical image segmentation was accepted as a spotlight at MIDL 2026.

Feb 2026

Paul Fischer defended his PhD

Paul Fischer successfully defended his PhD thesis on leveraging uncertainties in medical prediction systems.

Jan 2026
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