Chair of Artificial Intelligence and Machine Learning
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Stefan Haas

Stefan Haas, M.Sc.

PhD student (BMW)

Contact

Ludwig-Maximilians-Universität München
Institute of Informatics
Chair of Artificial Intelligence and Machine Learning
Prof. Dr. Eyke Hüllermeier
Akademiestr.7
80799 München


Website: ORCiD 0000-0001-9916-0060

Research Focus

Stefan is an external Ph.D. student doing an on-the-job Ph.D. at BMW.
His research is driven by an automotive use case at BMW (goodwill assessment), which is an example for prescriptive machine learning. As such, he is interested in challenges related to prescriptive machine learning, e.g., weak supervision and uncertainty representation.

Research Areas

Prescriptive Machine Learning, Weakly Supervised Learning, Uncertainty Quantification, Selective Classification, Ordinal Classification, Explainable AI (XAI)

Conference Talks and Papers

  • Stefan Haas, Eyke Hüllermeier (2022)
    A prescriptive machine learning approach for assessing goodwill in the automotive domain
    In: Proc. European Conference on Machine Learning and Knowledge Discovery in Databases – Applied Data Science Track