Jakob Schöffer, M.Sc.

Jakob Schöffer, M.Sc.

  • Kaiserstraße 89
    76133 Karlsruhe


Jakob is a research associate at the Applied AI Lab within the Karlsruhe Service Research Institute (KSRI). His interests include:

  • Algorithmic Decision Making
  • Fairness and Ethics in Artificial Intelligence
  • Human-Computer Interaction
  • Machine Learning and Natural Language Processing (general)
  • Mathematical Optimization (general)

Please reach out if you are interested in writing a bachelor or master thesis on one of these topics.

Curriculum Vitae

Jakob earned his undergraduate degree in Industrial Engineering and Management from the Karlsruhe Institute of Technology (KIT). In 2017, Jakob graduated from the Georgia Institute of Technology in Atlanta, Georgia (USA) with a master’s in Operations Research. Upon graduation, he joined IBM in Armonk, New York (USA), working as a data scientist. After more than 2 years with IBM, Jakob returned to KIT in October 2019, where he is now working towards his PhD.


Conference Papers
A Study on Fairness and Trust Perceptions in Automated Decision Making.
Schöffer, J.; Machowski, Y.; Kühl, N.
2021. Joint Proceedings of the ACM IUI 2021 Workshops, April 13–17, 2021, College Station, USA 
A Ranking Approach to Fair Classification.
Schöffer, J.; Kühl, N.; Valera, I.
2021. COMPASS ’21: Proceedings of the 4th ACM SIGCAS Conference on Computing and Sustainable Societies, June 28 - July 2, 2021, Virtual Event, Australia 
Book Chapters
Service Analytics: Putting the “Smart” in Smart Services.
Kühl, N.; Fromm, H.; Schöffer, J.; Satzger, G.
2020. Smart Service Management : Design Guidelines and Best Practices. Ed.: M. Maleshkova; N. Kühl, Axel Springer SE. doi:10.1007/978-3-030-58182-4
Conference Papers
Utilizing Adaptive AI-based Information Systems to Analyze the Effectiveness of Policy Measures in the Fight of COVID-19.
Baier, L.; Schöffer, J.; Kühl, N.
2020. ICIS 2020 – Making Digital Inclusive: Blending the Local and the Global : December 13-16, 2020 
DEAL: Deep Evidential Active Learning for Image Classification.
Hemmer, P.; Kühl, N.; Schöffer, J.
2020. 19th IEEE International Conference On Machine Learning And Applications, December, Miami, Florida, December 14-17, 2020, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ICMLA51294.2020.00141