Jakob Kappenberger
Research Interests
- Ethical implications of smart cities
- Agent-based traffic simulations
- Policy decisions based on Reinforcement Learning
Publications
- Cohausz, L., Kappenberger, J. and Stuckenschmidt, H. (2024). Combining fairness and causal graphs to advance both. In , Fairness and Bias in AI : Proceedings of the 2nd Workshop on Fairness and Bias in AI, co-located with 27th European Conference on Artificial Intelligence (ECAI 2024) (S. 1–14). CEUR Workshop Proceedings, RWTH Aachen: Aachen, Germany.
- Cohausz, L., Kappenberger, J. and Stuckenschmidt, H. (2024). What fairness metrics can really tell you: A case study in the educational domain. In , LAK'24: Proceedings of the 14th Learning Analytics and Knowledge Conference (S. 792–799). , Association for Computing Machinery: Kyoto, Japan.
- Kappenberger, J. and Stuckenschmidt, H. (2024). A framework for human-centered AI-based public policies. In Human-centered AI: A multidisciplinary perspective for policy-makers, auditors, and users (S. 287–303). Boca Raton: CRC Press.
- Kappenberger, J., Theil, K. and Stuckenschmidt, H. (2022). Evaluating the impact of AI-based priced parking with social simulation. In , Social Informatics: 13th International Conference, SocInfo 2022, Glasgow, UK, October 19–21, 2022, proceedings (S. 54–75). Lecture Notes in Computer Science, Springer: Berlin [u.a.].
Teaching
- AI in Industry (spring 2022 / spring 2023 / spring 2024, M.Sc.)
- CS 704 Social Simulation Seminar (spring 2022, spring 2023, M.Sc.)
- Team Project (fall 2022 -, M.Sc.)