Tom Oberhauser is a research assistant at DATEXIS since December 2018. He completed his Bachelor of Science Degree, as well as his Master of Science Degree in Media Informatics with distinction. Currently, he is working on the Smart-MD project.

Research Interests

  • Active Learning / Human in the Loop
  • Training Data Augmentation / Generation
  • Few-Shot / Zero-Shot Learning


  • Paul Grundmann, Tom Oberhauser, Felix Gers, Alexander Löser: Attention Networks for Augmenting Clinical Text with Support Sets for Diagnosis Prediction. COLING 2022
  • Tom Oberhauser, Tim Bischoff, Karl Brendel, Maluna Menke, Tobias Klatt, Amy Siu, Felix Alexander Gers and Alexander Löser: TrainX – Named Entity Linking with Active Sampling and Bi-Encoders. COLING 2020
  • Rudolf Schneider, Sebastian Arnold, Tom Oberhauser, Tobias Klatt, Thomas Steffek and Alexander Löser: Smart-MD: Neural Paragraph Retrieval of Medical Topics.World Wide Web Conference (Companion). IW3C2, 2018: 203–206 [PDF]
  • R. Schneider, S. Arnold, T. Oberhauser, T. Klatt, T. Steffek, A. Löser, "Smart-MD: Neural Paragraph Retrieval of Medical Topics", WWW ’18 Companion: The 2018 Web Conference Companion, April 23–27, 2018, Lyon, France. ACM, New York, NY, USA, 4 pages. [video]
  • R. Schneider, T. Oberhauser, T. Klatt, F. A. Gers, and A. Löser, “Analysing Errors of Open Information Extraction Systems,” BLGNLP 2017 Building Linguistically Generalizable NLP Systems at EMNLP 2017. [arXiv] [slides]
  • R. Schneider, T. Oberhauser, T. Klatt, F. A. Gers, and A. Löser, “RelVis: Benchmarking OpenIE Systems,” ISWC 2017 The 16th International Semantic Web Conference - Posters and Demos, p. to appear. [Video] [git]