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Humboldt-Universität zu Berlin - Wirtschaftswissenschaftliche Fakultät

Johannes Haupt


Telephone: +49 30 2093-99543

Email: johannes.haupt[at]hu-berlin.de

Office hours: Thursday, 10-12 (by appointment)

Room: SPA1, 335



Johannes Haupt holds a M.Sc. degree in Economics from Humboldt University in Berlin. In the course of his PhD, he develops machine learning applications in marketing. He is currently working on models for prescriptive decision support in the form of treatment effect estimation and causal machine learning. Johannes has been a research assistant at the chair of information systems since April 2016.


Research Interests

  • Causal Machine Learning / Uplift Modeling

  • Prescriptive Modeling and Decision Support

  • Deep Learning

  • Recommender Systems

  • Bayesian Machine Learning



Social Media



Other Interests



  • Haupt, J., Jacob, D., Gubela, R., & Lessmann, S. (2019). Affordable Uplift: Supervised Randomization in Controlled Experiments. ArXiv Preprint, arXiv:1910.00393. https://arxiv.org/abs/1910.00393
  • Haupt, Johannes, Bender, Benedict, Fabian, Benjamin & Lessmann, Stefan. (2018). Robust identification of email tracking: a machine learning approach. European Journal of Operational Research, 271(1), 341-356.
  • Baumann, Annika, Haupt, Johannes, Gebert, Fabian & Lessmann, Stefan. (2018). The Price of Privacy: An Evaluation of the Economic Value of Collecting Clickstream Data. Business & Information Systems Engineering. 10.1007/s12599-018-0528-2.
  • Lessmann, Stefan, Coussement, Kristof, W. De Bock, Koen & Haupt, Johannes. (2018). Targeting Customers for Profit: An Ensemble Learning Framework to Support Marketing Decision Making. SSRN Electronic Journal. 10.2139/ssrn.3130661.
  • Gubela, Robin, Lessmann, Stefan, Haupt, Johannes, Baumann, Annika, Radmer, Tillmann & Gebert, Fabian. (2017). Revenue Uplift Modeling. Proceedings of the thirty-eighth International Conference on Information Systems ICIS 2017
  • Baumann, Annika, Haupt, Johannes, Gebert, Fabian & Lessmann, Stefan. (2017). Changing Perspectives: Using Graph Metrics to Predict Purchase Probabilities. Expert Systems with Applications. 94. 10.1016/j.eswa.2017.10.046.
  • Bender, Benedict, Fabian, Benjamin, Lessmann, Stefan & Haupt, Johannes. (2016). E-Mail Tracking: Status Quo and Novel Countermeasures. Proceedings of the thirty-seventh International Conference on Information Systems, ICIS 2016




  • Business Analytics and Data Science Exercise (Winter term 16-19)
  • Advanced Data Analytics for Management Support (Summer term 19)
  • Seminar Causal Machine Learning (Applied Predictive Analytics) (Summer term 19)
  • Seminar Applied Predictive Analysis (Summer term 16-18)
  • Seminar Information Systems (Winter term 16-19)
  • Digital Marketing and Web Analytics Exercise (Summer term 17)



  • Strategie, Organisation und IT (Summer term 18)
  • Bachelorseminar Wirtschaftsinformatik (Summer term 18, 19)