Maximilian Zenk

Maximilian Zenk is a PhD student at the Division of Medical Image Computing (MIC) who works on federated data for medical image segmentation. He received his MSc in Physics from Heidelberg university where he specialised in computational physics and biologically plausible neural networks. His current research interests revolve around benchmarking the robustness of segmentation models to dataset shifts between medical centres and the automatic identification of failure cases in federated settings.

Projects:

• Federated Tumor Segmentation Challenge
• Failure analysis for semantic segmentation
• Trustworthy Federated Data Analytics

Interests:

• Federated learning and analyses
• Failure detection
• Semantic Segmentation