Alexander Berger

Alexander Berger is a Doctoral researcher at the Chair for Artificial Intelligence in Medicine at the Technical University of Munich (TUM). His main research focus is the development of deep learning methods for topology-preserving image segmentation and extracting and analyzing graph-structured information from medical images. Most of his applications aim at improving diagnosis and treatment of diseases. Furthermore, Alexander is interested in self- and weakly-supervised transfer learning and domain adaptation. He received his M.Sc. at TUM under Prof. Daniel Rückert.

Topics for BSc and MSc Thesis, Semester Projects, IDPs, Guided Research or any other student project can always be discussed on inquiry.

Interests:

• Topology-preserving Image Segmentation
• Weakly- and Self-supervised Transfer Learning
• Domain Adaptation

Education:

• Informatics (M. Sc.), 2023
  Technical University of Munich
• Information Systems (B. Sc.), 2020
  Technical University of Munich