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Robin Hirt

M.Sc. Robin Hirt

Wissenschaftlicher Mitarbeiter
Gruppe: Digital Service Innovation
Raum: 4B-05, Gebäude 05.20
Tel.: +49 721 608-45773
hirtUau7∂kit edu

 



Aktivitäten

Seit Januar 2017 ist Robin Hirt wissenschaftlicher Mitarbeiter der Gruppe Digital Service Innovation. In seiner Forschung beschäftigt er sich mit Analytics in verteilten Organisationen. Hierbei wird durch die Kombination von Meta und Transfer Learning das "Lernen in Systemen" ermöglicht. Er ist außerdem Mitgründer der prenode GmbH.

Forschungsinteressen

  • Applications and architectures for Meta Machine Learning & Transfer machine learning techniques in networks
  • Distributed Machine Learning  in Smart Service Systems & Industrie 4.0
  • Process and reference models for applying machine learning techniques in research

Teaching

  • 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)

Publikationen

Aufgrund der interdisziplinären Aktivitäten der KSRI-Mitglieder werden hier auch Publikationen gelistet, die nicht explizit im Rahmen der Tätigkeiten am KSRI entstanden sind.

2020
Proceedingsbeiträge
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
2019
Zeitschriftenaufsätze
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
Proceedingsbeiträge
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
Vorträge
How to Learn from Others? A Research Agenda on Transfer Machine Learning for Sales Forecasting.
Hirt, R.; Kühl, N.
2019, Februar 19. MIT-IBM Watson AI Lab (2019), Cambridge, MA, USA, 19. März 2019
2018
Proceedingsbeiträge
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
2017
Proceedingsbeiträge
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