By appointment (online or in presence)

• MSc Digital Business Engineering
• BSc Digital Business
• BSc und MSc Wirtschaftsinformatik

• Studiendekan MSc Digital Business Engineering
• Vorsitzender Prüfungsausschuss MSc Digital Business Engineering
• Verantwortlicher für die Lehre am Herman-Hollerith Lehr- und Forschungszentrum

• Internet of Things
• Computernetzwerke
• Software Engineering

Forschungsthemen

• Internet of Things (IoT)
• Data Products und Smart Data Service in datenintensiven Umgebungen  

• Seit 2015 Professor für Software und Service Engineering an der Fakultät Informatik
• 2010-2015 Teamleiter Statistiksoftware und Fahrgastzählung, INIT GmbH Karlsruhe
• Doktor der Ingenieurwissenschaften (Dr.-Ing.) 
• Diplom-Informatiker (Dipl.-Inform.)

• Klöser, S., Kotstein, S., Reuben, R., Zerrer, T., Decker, C. (2021). Deep Reinforcement Learning for IoT Interoperability. In: Weißgraeber, P., Heieck, F., Ackermann, C. (eds) Advances in Automotive Production Technology – Theory and Application. ARENA2036. Springer Vieweg, Berlin, Heidelberg. doi.org/10.1007/978-3-662-62962-8_23 
• Kotstein, S., Decker, C. (2020). Navigational Support for Non HATEOAS-Compliant Web-Based APIs. In: Dustdar, S. (eds) Service-Oriented Computing. SummerSOC 2020. Communications in Computer and Information Science, vol 1310. Springer, Cham. doi.org/10.1007/978-3-030-64846-6_10
• Kotstein, S., Decker, C. An Approach for Measuring IoT Interoperability Using Causal Modeling. Intelligent Environments 2019, Rabat, Morocco 2019 pp. 170 - 179, doi: 10.3233/AISE190039. 
• Kotstein S., Decker C., "Reinforcement Learning for IoT Interoperability," 2019 IEEE International Conference on Software Architecture Companion (ICSA-C), Hamburg, Germany, 2019, pp. 11-18, doi: 10.1109/ICSA-C.2019.00010.