Dr. Max Schemmer

  • Kaiserstr. 89

    D - 76133 Karlsruhe

Activities

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.

Publikationsliste


Towards Understanding AI Delegation: The Role of Self-Efficacy and Visual Processing Ability
Westphal, M.; Hemmer, P.; Vössing, M.; Schemmer, M.; Vetter, S.; Satzger, G.
2024. ACM Transactions on Interactive Intelligent Systems. doi:10.1145/3696423
From Competition to Complementarity: Foundations and Evidence for Effective Human-AI Collaboration. PhD dissertation
Schemmer, M. R.
2024, May 21. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000170595
Explainable Al for Expert Systems
Bode, J.; Schemmer, M.; Satzger, G.
2022. Wirtschaftsinformatik 2022 Proceedings, online, 2022
Towards Effective Human-AI Decision-Making: The Role of Human Learning in Appropriate Reliance on AI Advice
Schemmer, M.; Bartos, A.; Spitzer, P.; Hemmer, P.; Liebschner, J.; Satzger, G.; Kühl, N.
2023. International Conference on Information Systems, 17 S. doi:10.48550/arXiv.2310.02108
Sanitizing data for analysis: Designing systems for data understanding
Holstein, J.; Schemmer, M.; Jakubik, J.; Vössing, M.; Satzger, G.
2023. Electronic Markets, 33 (1), Art.-Nr.: 52. doi:10.1007/s12525-023-00677-w
Explainable AI for Constraint-Based Expert Systems
Bode, J.; Schemmer, M.; Balyo, T.
2022. Wirtschaftsinformatik 2022 Proceedings, online, 2022, Association for Information Systems (AIS)
Conceptualizing a Multi-Sided Platform for Cloud Computing Resource Trading
Haller, F.; Schemmer, M.; Kühl, N.; Holtmann, C.
2023. Proceedings of the 31st European Conference on Information Systems (ECIS), Kristiansand, Norway, June 11 - 16, 2023, Association for Information Systems (AIS)
Appropriate Reliance on AI Advice: Conceptualization and the Effect of Explanations
Schemmer, M.; Kühl, N.; Benz, C.; Bartos, A.; Satzger, G.
2023. IUI ’23: Proceedings of the 28th International Conference on Intelligent User Interfaces, 410–422, Association for Computing Machinery (ACM). doi:10.1145/3581641.3584066
Human-AI Collaboration: The Effect of AI Delegation on Human Task Performance and Task Satisfaction
Hemmer, P.; Westphal, M.; Schemmer, M.; Vetter, S.; Vössing, M.; Satzger, G.
2023. Proceedings of the 28th International Conference on Intelligent User Interfaces (IUI 2023), 453–463, Association for Computing Machinery (ACM). doi:10.1145/3581641.3584052
Artificial intelligence and machine learning
Kühl, N.; Schemmer, M.; Goutier, M.; Satzger, G.
2022. Electronic markets, 32 (4), 2235–2244. doi:10.1007/s12525-022-00598-0
A Meta-Analysis of the Utility of Explainable Artificial Intelligence in Human-AI Decision-Making
Schemmer, M.; Hemmer, P.; Nitsche, M.; Kühl, N.; Vössing, M.
2022. Proceedings of the 2022 AAAI/ACM Conference on AI, Ethics, and Society, 1st-3rd August, 2022, Oxford. Ed. Vincent Conitzer, 617–626, Association for Computing Machinery (ACM). doi:10.1145/3514094.3534128
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. Proceedings of the 30th European Conference on Information Systems (ECIS), Timișoara, RO, June 18 - 24, 2022, Association for Information Systems (AIS)
On the Effect of Information Asymmetry in Human-AI Teams
Hemmer, P.; Schemmer, M.; Kühl, N.; Vössing, M.; Satzger, G.
2022
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) , 1490–1499, IEEE Computer Society
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.
2021
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