Three papers accepted at ICML 2026 Main Conference
Our lab will be presenting three papers at the International Conference on Machine Learning (ICML) 2026:
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Dynamic Decision Learning: Test-Time Evolution for Abnormality Grounding in Rare Diseases
Jun Li, Mingxuan Liu, Jiazhen Pan, Che Liu, Wenjia Bai, Cosmin I. Bercea, Julia A. Schnabel
(https://arxiv.org/pdf/2604.24972) -
No Data? No Problem: Robust Vision-Tabular Learning with Missing Values
Marta Hasny, Laura Daza, Keno Bressem, Maxime Di Folco, Julia Schnabel
(https://arxiv.org/pdf/2512.19602) -
Optimal Conversion from Renyi Differential Privacy to f-Differential Privacy
Anneliese Riess, Juan Felipe Gomez, Flavio du Pin Calmon, Julia A. Schnabel, Georgios Kaissis
(https://arxiv.org/pdf/2602.04562)
Julia A. Schnabel
Professor for Computational Imaging and AI in Medicine, Director of the Institute of Machine Learning in Biomedical Imaging
My research interests include machine/deep learning, nonlinear motion modeling, as well as multimodal and quantitative imaging, for cancer-, cardiac-, neuro- and perinatal imaging.
Cosmin I. Bercea
Research Scientist
I am a postdoctoral researcher specializing in vision and multimodal learning for medical image analysis, with the current focus on developing vision-language models for generative downstream tasks.
Laura Daza
Research Scientist
My research interests include machine learning for medical image segmentation.
Maxime Di Folco
Professor
My research interest is the study of the cardiac function via machine learning methods, in particular representation learning methods that aim to acquire low dimensional representation of high dimensional data. I have a strong interest in cardiac remodelling (adaptation of the heart to its environment or a disease), notably the study of the deformation and shape aspects.
Marta Hasny
Doctoral Researcher
My research interests include the application of foundation models and generative AI in cardiology.
Georgios Kaissis
Professor
His research concentrates on biomedical image analysis with a focus on next-generation privacy-preserving machine learning methods as well as probabilistic methods for the design and deployment of robust, secure, fair and transparent machine learning algorithms to medical imaging workflows.
Jun Li
Doctoral Researcher
My research interests include Vision and Language, Multi-Modal Learning, and Cross-Modality Generation.
Anneliese Riess
Doctoral Researcher
My research interests include mathematical foundations of privacy preserving artificial intelligence.