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Welcome to the Clinical Learning Systems research group!
About Us
Researchers and students in the Clinical Learning Systems (CLS) group develop reliable and privacy-preserving AI methods for analyzing clinical data, including medical images, text, and speech. CLS is led by Soroosh Tayebi Arasteh and focuses on verifiable clinical decision support, learning from model-generated supervision, representation learning, and privacy-preserving deep learning.
Research Directions
We work across vision, language, and speech at hospital scale. The methods are retrieval-augmented agents, self-supervision under model-generated labels, the geometry of frozen encoders, and differentially private training.
Latest news
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August 28, 2026
The ARISTOTLE proposal to the Federal Ministry of Research, Technology and Space is approved. Over the next 3 years the group will work on it with the Technical University of Munich and the University Hospital of TUM.
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August 26, 2026
RSNA published an interview with Soroosh on how cognitive biases mislead radiology language models. Read it
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June 9, 2026
The group presented 6 abstracts at Baiosphere Medical 2026 in Erlangen.