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Robin Hirt

M.Sc. Robin Hirt

Wissenschaftlicher Mitarbeiter
Group: Digital Service Innovation
Room: 4B-05, Gebäude 05.20
Phone: +49 721 608-45773
hirtZuy5∂kit edu



Since January 2017, Robin Hirt has been a research associate at Applied AI Labs. His research focuses on the development of artificial intelligence based on distributed data sets while taking data confidentiality into account. Mr. Hirt solved practical problems in several fields of application with artificial intelligence using design oriented methods.

The combination of Meta and Transfer Machine Learning enables "learning" in systems of complex companies. He founded prenode GmbH in 2018 and brings research from the field of Applied AI into practice as managing director.


  • Meta Machine Learning
  • Transfer machine learning in networks
  • Complex Event Processing, Stream Analytics
  • Explainable AI


  • Digital Services (SS19)
  • Artificial Intelligence in Service Systems (WS18/19)
  • Foundations of Digital Services A (SS18)
  • Foundations of Digital Services A (SS17)
  • Seminar: Applied Machine Learning and Microservices (SS17)


Due to the interdisciplinary activities of KSRI researchers publication lists also contain publications that have not explicitly been developed in the course of their activities at KSRI.

Conference Papers
How to Learn from Others: Transfer Machine Learning with Additive Regression Models to Improve Sales Forecasting.
Hirt, R.; Kühl, N.; Peker, Y.; Satzger, G.
2020. IEEE International Conference on Business Informatics (CBI), IEEE
A network-based transfer learning approach to improve sales forecasting of new products.
Karb, T.; Kühl, N.; Hirt, R.; Glivici-Cotruță, V.
2020. European Conference on Information Systems (ECIS) - Marrakech, Marocco, June 15 - 17, 2020
Half-empty or half-full? A Hybrid Approach to Predict Recycling Behavior of Consumers to Increase Reverse Vending Machine Uptime.
Walk, J.; Hirt, R.; Kühl, N.; Hersløv, E. R.
2020. Exploring Service Science : 10th International Conference on Exploring Service Science, IESS 2020, Porto, Portugal, February 05-07, 2020. Proceedings. Ed.: H. Nóvoa, Springer International Publishing, Basel
Journal Articles
Cognitive computing for customer profiling: meta classification for gender prediction.
Hirt, R.; Kühl, N.; Satzger, G.
2019. Electronic markets, 29 (1), 93–106. doi:10.1007/s12525-019-00336-z
Conference Papers
Service Systems, Smart Service Systems and Cyber-Physical Systems—What’s the difference? Towards a Unified Terminology.
Martin, D.; Hirt, R.; Kühl, N.
2019. 14. Internationale Tagung Wirtschaftsinformatik 2019 (WI 2019), Siegen, Germany, February 24-27
Machine Learning in Artificial Intelligence: Towards a Common Understanding [in press].
Kühl, N.; Goutier, M.; Hirt, R.; Satzger, G.
2019. Hawaii International Conference on System Sciences (HICSS-52), Grand Wailea, Maui, Hawaii, Januar 8-11, 2019
How to Learn from Others? A Research Agenda on Transfer Machine Learning for Sales Forecasting.
Hirt, R.; Kühl, N.
2019, February 19. MIT-IBM Watson AI Lab (2019), Cambridge, MA, USA, March 19, 2019
Conference Papers
Cognition in the Era of Smart Service Systems: Inter-organizational Analytics through Meta and Transfer Learning.
Hirt, R.; Kühl, N.
2018. 39th International Conference on Information Systems, ICIS 2018; San Francisco Marriott MarquisSan Francisco; United States; 13 December 2018 through 16 December 2018, AIS, New York (NY)
Towards Service-oriented Cognitive Analytics for Smart Service Systems.
Hirt, R.; Kühl, N.; Schmitz, B.; Satzger, G.
2018. Hawaii International Conference on System Sciences (HICSS-51), Waikoloa Village, Hawaii, United States, 3rd - 6th January 2018
Conference Papers
How to Cope With Incomplete Prediction Input? A Categorization of Techniques For Realizing Robust Analytics for Smart Service Systems.
Hirt, R.
2017. 3rd Karlsruhe Service Summit Research Workshop, Karlsruhe, Germany, 21st - 22nd September 2017
Abbildung kognitiver Fähigkeiten mit Metamodellen.
Hirt, R.; Kühl, N.
2017. INFORMATIK 2017, 47. Jahrestagung der Gesellschaft für Informatik, Chemnitz, Deutschland, 25. - 29. September 2017. Hrsg.: Maximilian Eib, 2301–2307, Gesellschaft für Informatik e.V., Bonn. doi:10.18420/in2017_231
An End-to-End Process Model for Supervised Machine Learning Classification : From Problem to Deployment in Information Systems.
Hirt, R.; Kühl, N.; Satzger, G.
2017. Designing the Digital Transformation, DESRIST 2017 Research in Progress Proceedings of the 12th International Conference on Design Science Research in Information Systems and Technology, Karlsruhe, Germany, 30th May - 1st June 2017. Ed.: A. Mädche, 55–63, KIT, Karlsruhe