Karl Fehrs, Ph.D.

Logo des Fachgebiets Resiliente Energiesysteme

Büro: NEOS 4280
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Research fellow (postdoctoral researcher) in hyBit Project, Research Group Resilient Energy Systems

Since 08/2025

Research associate at the department of Resilient Energy Systems, Faculty 4, University of Bremen

02/2021 - 01/2025

Ph.D. student at the Computer Science department of Aarhus University, Denmark

Advised by Prof. Ioannis Caragiannis. Thesis "Optimization and Learning in Voting"

01/2023 

M.Sc. degree in Computer Science, Aarhus University

02/2018 - 01/2021

Master's studies in Computer Science at Goethe University Frankfurt
Erasmus+ stay at Aarhus University, Denmark (Fall 2020)

02/2018 

B.Sc. degree in Computer Science, Goethe University Frankfurt

 

  • Computational social choice
  • Mathematical optimization
  • Energy systems & markets

  • Caragiannis I.; Fehrs K. (2024). Beyond the worst case: Distortion in impartial culture electorates. In: Proceedings of the 20th Conference on Web and Internet Economics (WINE). Forthcoming. (Full manuscript: arXiv:2307.07350)
  • Burkhardt J.; Caragiannis I.; Fehrs K.; Russo M.; Schwiegelshohn C.; Shyam S (2024). Low-distortion clustering with ordinal and limited cardinal information. In: Proceedings of the AAAI Conference on Artificial Intelligence, pp. 9555–9563. https://doi.org/10.1609/aaai.v38i9.28811
  • Caragiannis I.; Fehrs K. (2024). Beyond the worst case: Distortion in impartial culture electorates. In: Proceedings of the 20th Conference on Web and Internet Economics (WINE). Forthcoming. (Full manuscript: arXiv:2307.07350)
  • Burkhardt J.; Caragiannis I.; Fehrs K.; Russo M.; Schwiegelshohn C.; Shyam S (2024). Low-distortion clustering with ordinal and limited cardinal information. In: Proceedings of the AAAI Conference on Artificial Intelligence, pp. 9555–9563. https://doi.org/10.1609/aaai.v38i9.28811