M.Sc. Kathrin Donandt

M.Sc.Research Associate


Federal Waterways Engineering and Research Institute
Kußmaulstraße 17
76187 Karlsruhe
Phone: +49 721 9726-3740
E-Mail.: ‌ kathrin.donandt[at]baw.de


  • Present Position
    Research Associate
  • Professional Activity
    Collaboration in “SixDoF+AIS”, a cooperation project between the University Duisburg-Essen and the Federal Waterways Engineering and Research Institute
  • Past Positions
    2019-2020           Computer Scientist
    2017-2019           Research Associate
  • Education
    2015-2017           M.Sc Computer Science
    2012-2015           B.Sc Computer Science
    2011-2014           B.A Political Science


Conference Papers (peer-review)

  • Chiarcos, C., Donandt, K., Sargsian, H., Ionov, M. and Wichers-Schreur, J.
    Towards LLOD-based Language Contact Studies. A Case Study in Interoperability,
    Proc. of the 6th Workshop on Linked Data in Linguistics (LDL-2018): Towards Linguistic Data Science. European Language Resources Association (ELRA), Paris, France, Miyazaki, Japan, May 2018.
  • Chiarcos, C., Donandt, K., Ionov, M., Rind-Pawlowski, M., Sargsian, H., Wichers-Schreur, J., Abromeit, F. and Fäth, C.
    Universal Morphologies for the Caucasus region“,
    Proc. Of the 11th International Conference on Language Resources and Evaluation (LREC 2018). European Language Resources Association (ELRA), Paris, France, Miyazaki, Japan, May 2018.
  • Donandt, K., Chiarcos C. and Ionov M.
    Using Machine Learning for Translation Inference Across Dictionaries
    In: John P. McCrae, Francis Bond, Paul Buitelaar, Philipp Cimiano, Thierry Declerck, Jorge Gracia, Ilan Kernerman, Elena Montiel Ponsoda, Noam Ordan, and Maciej Piasecki (eds.)
    LDK Workshops 2017. Proceedings of the Shared Task on Translation Inference Across Dictionaries (TIAD 2017), held in conjunction with the First International Conference on Language, Data and Knowledge (LDK-2017). Galway, Ireland, June 2017, 103-112. 
  • Schenk, N., Chiarcos C., Donandt, K., Rönnqvist S., Stepanov, E. and Riccardi, G.
    Do We Really Need All Those Rich Linguistic Features? A Neural Network-Based Approach to Implicit Sense Labeling,
    Proc. of the CoNLL-16 shared task on Multilingual Shallow Discourse Parsing, held in conjunction with ACL-2016. Association for Computational Linguistics, Berlin, Germany, August 2016 (DOI: 10.18653/v1/K16-2005), 41-49.