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Information Systems and Applied Computer Sciences

Information Systems and Energy Efficient Systems

  1.  University of bamberg
  2. Faculties
  3. Information Systems and Applied Computer Sciences
  4. Subject groups
  5. Information Systems
  6. Information Systems and Energy Efficient Systems
  7. Team
  8. Felix Haag, M.Sc.

Felix Haag

Room: WE5/02.053

Telephone: +49 951 863 1996

Email: felix.haag(at)uni-bamberg.de

Consultation hour: by appointment

Career

  • 2021 - today: PhD student at the Energy Efficient Systems Group, Otto-Friedrich University of Bamberg
  • 2020 - today: Scientific assistant at the Energy Efficient Systems Group, Otto-Friedrich University of Bamberg
  • 2018 - 2021: Information Systems (M.Sc.), Otto-Friedrich-University of Bamberg – Degree with distinction
  • 2017: Internship at Mercedes-Benz Malaysia in Kuala Lumpur
  • 2015 - 2018: Information Systems (B.Sc.), Baden-Württemberg Cooperative State University in cooperation with Mercedes-Benz Tech Innovation

Research Interests

  • Explainable AI
  • Learning Analytics
  • Information Systems and Applications of Energy Informatics

Publications

Haag, F., Günther, S. A., Hopf, K., Handschuh, P., Klose, M., Staake, T. (2023): Addressing Learners' Heterogeneity in Higher Education: An Explainable AI-based Feedback Artifact for Digital Learning Environments. Wirtschaftsinformatik 2023, Paderborn, Germany (forthcoming)

Giacomazzi, E., Haag, F., Hopf, K. (2023): Short-term Electricity Load Forecasting using the Temporal Fusion Transformer: Effect of Grid Hierarchies and Data Sources. International Conference on Future Energy Systems (ACM e-Energy) 2023, Orlando, Florida, USA [preprint]

Günther, S. A., Haag, F., Hopf, K., Handschuh, P., Klose, M., Staake, T. (2022): A feedback component that leverages counterfactual explanations for smart learning support. Digitale Kulturen der Lehre entwickeln – Rahmenbedingungen, Konzepte und Werkzeuge (Springer VS Reihe: Perspektiven der Hochschuldidaktik) (forthcoming)

Haag, F., Hopf, K., Menelau Vasconcelos, P., Staake, T. (2022): Augmented Cross-Selling Through Explainable AI – A Case From Energy Retailing. European Conference on Information Systems (ECIS) 2022, Timișoara, Romania [link]

Wastensteiner, J., Weiss, T., Haag, F., Hopf, K. (2021): Explainable AI for Tailored Electricity Consumption Feedback – An Experimental Evaluation of Visualizations. European Conference on Information Systems (ECIS) 2021, Marrakech, Morocco [link]

Talks and workshops

Haag, F. (2022): Explainable Machine Learning to Augment Human Decision-Making. Doctoral Consortium during the 30th European Conference on Information Systems (ECIS), Timișoara, Romania, June 19

Hopf, K., Haag, F. (2020): Explainable AI for Enhanced Human-AI Interaction. Pre-ICIS Practice Development Workshop “AI Beyond the Hype”, Online, December 13