Stefano Woerner

PhD student - University of Tübingen

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Stefano Woerner started his PhD in the Machine Learning for Medical Image Analysis Group in September 2021. He works on meta-learning and few-shot learning for medical imaging and is interested in developing more “human-like” machine learning methods for medical image analysis.

Before joining the Machine Learning for Medical Image Analysis Group, Stefano obtained his Bachelor’s degree in Computer Science from University of Konstanz and his Master’s degree in Computer Science from ETH Zürich, focusing mainly on Machine Leanring and on Computer Vision.

Education

M.Sc. Computer Science | ETH Zürich | 2020
B.Sc. Computer Science | University of Konstanz | 2017


Stefano’s publications in our group

Navigating Data Scarcity Using Foundation Models: A Benchmark of Few-Shot and Zero-Shot Learning Approaches in Medical Imaging

Navigating Data Scarcity Using Foundation Models: A Benchmark of Few-Shot and Zero-Shot Learning Approaches in Medical Imaging
Stefano Woerner, Christian F. Baumgartner
Lecture Notes in Computer Science, 30-39 (2024)

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A comprehensive and easy-to-use multi-domain multi-task medical imaging meta-dataset

A comprehensive and easy-to-use multi-domain multi-task medical imaging meta-dataset
Stefano Woerner, Arthur Jaques, Christian F. Baumgartner
Scientific Data, 12, 666 (2025)

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MedIMeta: An easy-to-use meta-dataset for medical imaging applications
Stefano Woerner, Arthur Jaques, Christian F. Baumgartner
Medical Imaging with Deep Learning (short paper) (2024)

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Attri-Net: A Globally and Locally Inherently Interpretable Model for Multi-Label Classification Using Class-Specific Counterfactuals

Attri-Net: A Globally and Locally Inherently Interpretable Model for Multi-Label Classification Using Class-Specific Counterfactuals
Susu Sun, Stefano Woerner, Andreas Maier, Lisa M Koch, Christian F. Baumgartner
Journal of Machine Learning for Biomedical Research (MELBA) (2024)

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Inherently interpretable multi-label classification using class-specific counterfactuals

Inherently interpretable multi-label classification using class-specific counterfactuals
Susu Sun, Stefano Woerner, Andreas Maier, Lisa M Koch, Christian F. Baumgartner
Proceedings of Machine Learning Research, 227, 937-956 (2023)

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Strategies for Meta-Learning with Diverse Tasks
Stefano Woerner, Christian F. Baumgartner
Medical Imaging with Deep Learning (short paper) (2022)

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