Sebastian Pölsterl

Post-Doctoral Researcher

I’m a researcher at the lab for Artificial Intelligence in Medical Imaging working on machine learning for biomedical applications. My research interests are time-to-event analysis (survival analysis) and using deep learning techniques to learn from non-Euclidean data such as graphs. Previously, I worked at The Institute of Cancer Research, London and was among the winners of the Prostate Cancer DREAM challenge. I’m the author of scikit-survival, a machine learning library for survival analysis built on top of scikit-learn.


  • Time-to-event analysis
  • Non-Euclidean data
  • High-dimensional data
  • Biomedical applications
  • Deep learning


  • PhD in Computer Science, 2016

    Technische Universität München

  • MSc in Bioinformatics, 2011

    Ludwig-Maximilians-Universität & Technische Universität München

  • BSc in Bioinformatics, 2008

    Ludwig-Maximilians-Universität & Technische Universität München