Felix Haag

Room: WE5/02.053

Telephone: +49 951 863 1996

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

Consultation hour: by appointment


  • 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
  • 2023 (Nov): Research stay at the Institute of Technology Management (ITEM), University of St. Gallen
  • 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

  • Human-AI Collaboration
  • Explainable AI
  • Learning Analytics


  • Best Paper Award (International Conference on Wirtschaftsinformatik 2023)
  • Award of the “Stiftung Energieinformatik” in the category “Best Master Thesis”


Bayer, D., Haag, F., Pruckner, M., Hopf, K. (2024): Electricity Demand Forecasting in Future Grid States: A Digital Twin-Based Simulation Study. International Conference on Smart and Sustainable Technologies (IEEE SpliTech) 2024, Bol, Croatia (forthcoming)

Günther, S. A., Haag, F., Hopf, K., Handschuh, P., Klose, M., Staake, T. (2024): 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) [link]

Haag, F., Stingl, C., Zerfass, K., Hopf, K., Staake, T. (2023): Overcoming Anchoring Bias: The Potential of AI and XAI-based Decision Support. International Conference on Information Systems 2023, Hyderabad, India [link]

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 [link]

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 [link]

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 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 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