Karl Fehrs, Ph.D.
Büro: NEOS 4280
Tel:
E-Mail
Research associate (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. (2022). The complexity of learning approval-based multiwinner voting rules. In: Proceedings of the AAAI Conference on Artificial Intelligence, pp. 4925–4932. https://doi.org/10.1609/aaai.v36i5.20422 (Full manuscript: arXiv:2110.00254)