Max Schemmer, M.Sc.

Max Schemmer, M.Sc.

  • Kaiserstr. 89
    76133 Karlsruhe


Max is a research associate at the Applied AI Lab within the Karlsruhe Service Research Institute (KSRI).

His research interests include:

  • Applied Artificial Intelligence
  • Applied Machine Learning & Deep Learning
  • AI-based Services / Servitization
  • Human-Machine-Collaboration
  • Industry 4.0
  • Computer Vision

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

Curriculum Vitae

Max Schemmer earned his Bachelor's degree in Economics at the University of Cologne. He graduated with a Master's degree in Economics Engineering from the Karlsruhe Institute of Technology (KIT). As part of the master's degree, he studied at the University of Southern Denmark with a focus on data science and robotics. From August 2020 he is working on his PhD in cooperation with IBM in the Applied AI Lab of the Digital Service Innovation group. During his doctorate he is working on the topic AI-based Servitization.


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
On the Influence of Explainable AI on Automation Bias
Schemmer, M.; Kühl, N.; Benz, C.; Satzger, G.
2022. Proceedings of the 30th European Conference on Information Systems (ECIS), Timișoara, RO, June 18 - 24, 2022, Association for Information Systems (AIS)
Intelligent Decision Assistance Versus Automated Decision-Making: Enhancing Knowledge Work Through Explainable Artificial Intelligence
Schemmer, M.; Kühl, N.; Satzger, G.
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
Detecting Daytime Bruxism Through Convenient and Wearable Around-the-Ear Electrodes
Knierim, M.; Schemmer, M.; Woehler, D.
2021. Advances in Usability, User Experience, Wearable and Assistive Technology – Proceedings of the AHFE 2021 Virtual Conferences on Usability and User Experience, Human Factors and Wearable Technologies, Human Factors in Virtual Environments and Game Design, and Human Factors and Assistive Technology, July 25-29, 2021, USA. Ed.: T. Ahram, 26–33, Springer. doi:10.1007/978-3-030-80091-8_4
Predicting In-Field Flow Experiences Over Two Weeks From ECG Data: A Case Study
Knierim, M.; Pieper, V.; Schemmer, M.; Loewe, N.; Reali, P.
2021. Information Systems and Neuroscience: NeuroIS Retreat 2021. Ed.: F. D. Davis, 107–117, Springer. doi:10.1007/978-3-030-88900-5_11
Exploring the Recognition of Facial Activities Through Around-the-Ear Electrode Arrays (cEEGrids)
Knierim, M.; Schemmer, M.; Perusquía-Hernández, M.
2021. Information Systems and Neuroscience: NeuroIS Retreat 2021. Ed.: F. D. Davis, 47–55, Springer. doi:10.1007/978-3-030-88900-5_6
IBM Service Transformation: From product suppliers to service providers
Brandes, M.; Osthues, S.; Bach, M.; Schel, P.; Büsching, A.; Schmidt, U.; Monger, M.; Schnürer, F.; Müller, P.; Satzger, G.; Kühl, N.; Vössing, M.; Schemmer, M.
Conceptualizing Digital Resilience for AI-Based Information Systems
Schemmer, M.; Heinz, D.; Baier, L.; Vössing, M.; Kühl, N.
2021. Proceedings of the 29th European Conference on Information Systems (ECIS), June 14 - 16, 2021