Dr. Konstantin Hopf

Room: WE5/02.062
Phone: +49 951 863 2236
Email: konstantin.hopf(at)uni-bamberg.de
Consultation hours by appointment
Academic Career
(The Bachelor's thesis received first place in the IT Cluster Oberfranken e.V. graduation award.)
Room: WE5/02.062
Phone: +49 951 863 2236
Email: konstantin.hopf(at)uni-bamberg.de
Consultation hours by appointment
Development and responsibility of the master courses "Business Intelligence & Analytics" (EESYS-BIA-M, V/?, 6 ECTS, winter term), "Data-driven Decision Support" (EESYS-DDS-M, V/?, 6 ECTS, summer term), master seminar "Platforms of Human-AI Collaboration" (WS 2020/21, 3 ECTS)
Supervision of over 90 Bachelor's and Master's theses, as well as student project papers in the Information Systems programs at the University of Bamberg
Representative of the scientific staff of the Faculty WIAI in the Faculty Council and the Mittelbau-Konvent (2017-2019 and 2019-2021)
Lectureship for the course "Business Analytics: Technologies, Methods, and Concepts" at the University of Erlangen-Nuremberg and the course "Business Intelligence" for master programs Strategic Management and Consulting at CBS International Business School, Mainz (since summer term 2021)
Individual applications of (explainable) machine learning for decision support, e.g. energy retailing, energy efficiency, higher education teaching
Organizational value creation through (explainable) machine learning applications
Data work in companies
Stingl, C., Hopf, K., Staake, T. (2018). Explaining and predicting annual electricity demand of enterprises – A case study from Switzerland, 7. DACH+ Conference on Energy Informatics, Oldenburg, Germany, October 11 – 12, In: Energy Informatics, 1:50, DOI: 10.2314/KXP:1687331642
Sodenkamp, M., Hopf, K., Kozlovskiy, I., Staake, T. (2016). Smart-Meter-Datenanalyse für automatisierte Energieberatungen ("Smart Grid Data Analytics"), Final project report. Bundesamt für Energie, Schweiz (Online)
Sodenkamp, M., Hopf, K., Staake, T. (2015). Using supervised machine learning to explore energy consumption data in private sector housing. In: Tavana, M. & Puranam, K. (Eds.): Handbook of Research on Organizational Transformations through Big Data Analytics. Hershey, USA: IGI Global, DOI: 10.4018/978-1-4666-7272-7.ch019