In recent years, there has been a rising demand for transparent and explainable machine learning (ML) models. Although significant progress has been made in generating different types of explanations for ML models, this topic has received minimal attention in the operations research (OR) community, due to a larger focus by the public on societal effects of data-driven ML models. However, algorithmic decisions in OR are made by complex algorithms, which also lack explainability. The main goal of this PhD project is to build the foundation for explainable decision making.
In this research, the candidate will define a general mathematical framework for explainable decision making and introduce models to provide explanations for different classes of optimization problems. Solution algorithms will be developed and tested on real-world instances of operations research problems.
For more information: https://vacatures.uva.nl/UvA/job/PhD-in-Explainable-Decision-Making/786835302/
If you have any questions, please contact Jannis Kurtz: j.kurtz@uva.nl
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