Patrick Hemmer, M.Sc.

Patrick Hemmer, M.Sc.

  • Kaiserstr. 89
    76133 Karlsruhe


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

  • Human-Centered Artificial Intelligence
  • Machine Learning & Deep Learning
  • Human-AI Complementarity

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

Curriculum Vitae

Patrick graduated from the Karlsruhe Institute of Technology (KIT) with a bachelor’s and a master’s degree in Industrial Engineering and Management. As part of the master’s degree, he studied for one year at the University of Linköping in Sweden and participated in the Service Design Thinking program of the KSRI.

Community Services

Reviewer at:

  • European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Database
  • AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society
  • Business & Information Systems Engineering
  • European Conference on Information Systems
  • Hawaii International Conference on System Sciences


Forming Effective Human-AI Teams: Building Machine Learning Models that Complement the Capabilities of Multiple Experts
Hemmer, P.; Schellhammer, S.; Vössing, M.; Jakubik, J.; Satzger, G.
2022. Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2478–2484, International Joint Conferences on Artificial Intelligence Organization (IJCAI). doi:10.24963/ijcai.2022/344
On the Effect of Information Asymmetry in Human-AI Teams
Hemmer, P.; Schemmer, M.; Kühl, N.; Vössing, M.; Satzger, G.
Designing Resilient AI-based Robo-Advisors: A Prototype for Real Estate Appraisal
Schemmer, M.; Hemmer, P.; Kühl, N.; Schäfer, S.
2022. 17th International Conference on Design Science Research in Information Systems and Technology, 1st - 3rd June 2022, St. Petersburg, FL, USA
Factors that Influence the Adoption of Human-AI Collaboration in Clinical Decision-Making
Hemmer, P.; Schemmer, M.; Riefle, L.; Rosellen, N.; Vössing, M.; Kühl, N.
2022. Association for Information Systems (AIS). doi:10.5445/IR/1000146871
Instance Selection Mechanisms for Human-in-the-Loop Systems in Few-Shot Learning
Jakubik, J.; Blumenstiel, B.; Vössing, M.; Hemmer, P.
2022. Wirtschaftsinformatik 2022 : Proceedings. Bd.: 6, AIS eLibrary (AISeL)
Designing a Human-in-the-Loop System for Object Detection in Floor Plans
Jakubik, J.; Hemmer, P.; Vössing, M.; Blumenstiel, B.; Bartos, A.; Mohr, K.
2022. Proceedings of the 36th Annual Conference on Innovative Applications of Artificial Intelligence (IAAI 2022), Online, 22.02.2022-01.03.2022, 12524–12530, Association for the Advancement of Artificial Intelligence (AAAI). doi:10.1609/aaai.v36i11.21522
Utilizing Active Machine Learning for Quality Assurance: A Case Study of Virtual Car Renderings in the Automotive Industry
Hemmer, P.; Kühl, N.; Schöffer, J.
2022. Proceedings of the Hawaii International Conference on Systems Sciences (HICSS-55)
Human-AI Complementarity in Hybrid Intelligence Systems: A Structured Literature Review
Hemmer, P.; Schemmer, M.; Vössing, M.; Kühl, N.
2021. PACIS 2021 Proceedings
Object Detection in Floor Plans: Lessons From Designing a Human-in-the-Loop System
Hemmer, P.; Vössing, M.; Blumenstiel, B.
2021, March 24. Artificial Intelligence in Architecture, Engineering and Construction (2021), Online, March 24–25, 2021
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