Prof. Dr. Christoph Lippert

Benjamin Bergner, M.Sc.

PhD Student

Phone: +49 331 5509-4823

Room: Campus III - Building G2 - G-2.1.34

Email: benjamin.bergner(at)hpi.de

Web: LinkedIn -- Twitter -- Researchgate -- Google Scholar

Research Interests

  • Computer vision and machine learning methods
  • Development of methods for application factors in computer vision, such as interpretability, managing high-resolution images, inclusion of domain knowledge, etc.
  • Applying deep learning to vision problems in digital health

Thesis supervision


  • Martin Gerstmaier, M.Sc. IT Systems Engineering, HPI, Self-Attention in Medical Imaging 
  • Marius Pullig, M.Sc., TU Berlin, Deep learning models for 3D MRI brain classification: a multi-sequence comparison
  • DuyHung Nguyen, M.Sc. IT Systems Engineering, HPI, Building a Text Embedding Model for the Imaging Research Warehouse at Mount Sinai
  • Tim Henning, M.Sc. IT Systems Engineering, HPI, HistoFlow: Label-Efficient and Interactive Deep Learning Cell Analysis


  • Ahmed Rekik (M.Sc. IT Systems Engineering, HPI), Learning liver and tumor segmentation with small annotated datasets


  • M.Sc. Digital Engineering, Otto-von-Guericke-Universität Magdeburg (2018)
    • Grade: 1.3, best of class 2018
    • Thesis: Automatic Landmark Detection for Preoperative Planning of Hip Surgery using Image Processing and Convolutional Neural Networks, in collaboration with Sectra Medical (Linköping, Sweden), Link
  • Semester abroad, Information systems, Universidade Federal de Santa Catarina, Brazil (2017)
  • B.Sc. Industrial Engineering, Otto-von-Guericke-Universität Magdeburg (2015)
    • Grade: 1.8
    • Thesis: Design and development of a Car2Car communication interface for
      autonomous vehicles


Peer-reviewed conference articles

  • Da Cruz, H. F., Bergner, B., Konak, O., Schneider, F., Bode, P., Lempert, C., & Schapranow, M. P. (2019, October). MORPHER-A Platform to Support Modeling of Outcome and Risk Prediction in Health Research. In 2019 IEEE 19th International Conference on Bioinformatics and Bioengineering (BIBE) (pp. 462-469). IEEE Computer Society. Link
  • Oleynik, M., Faessler, E., Sasso, A. M., Kappattanavar, A., Bergner, B., Da Cruz, H. F., ... & Böttinger, E. P. (2018, November). HPI-DHC at TREC 2018 Precision Medicine Track. In TREC. Link
  • Bergner, B., & Krempl, G. (2016). Active Subtopic Detection in Multitopic Data. In AL@ iKNOW (pp. 35- 44). Link


  • Taleb, A., Loetzsch, W., Danz, N., Severin, J., Gaertner, T., Bergner, B., & Lippert, C. (2020). 3D Self-Supervised Methods for Medical Imaging. arXiv preprint arXiv:2006.03829. Link
  • Henning, T., Bergner, B., & Lippert, C. (2020). HistoFlow: Label-Efficient and Interactive Deep Learning Cell Analysis. bioRxiv. Link