Prof. Dr. Christoph Lippert

Aiham Taleb, M.Sc.

Research Assistant, PhD Candidate

Phone: +49 159 01093064

Room: G-2.1.32

Email: aiham.taleb(at)hpi.de

Research Interests

Improving the data efficiency of machine (deep) learning methods through multi-modal self-supervised (unsupervised) algorithms. Aiming at significantly reducing the human annotation required for medical application

Research Projects

  • Multimodal Self-Supervised Learning for Medical Image Analysis: we propose a novel self-supervised multimodal puzzle-solving proxy task, which facilitates neural network representation learning from multiple image modalities. 
  • 3D Self-Supervised Methods for Medical Imaging: we propose five different methods, which facilitate feature learning from unlabeled 3D scans.
  • Strong multimodal alignment of image and text patient data samples from a large real-world clinical corpus with a variety of cases. Aiming at improving disease detection, disease reporting, and annotation efficiency.


Click on the "publications" word above to access the full list of publications