AI for Decision-Making (AI4DM) develops methods, techniques and tools for AI-driven decision making in operational business process. This involves advanced analysis of business process and optimization of operational decisions in logistics, manufacturing, e-commerce, and healthcare.
Specific tools, methods, and techniques that are being developed include:
- tools for intelligent decision support for humans, using different modalities of data from multiple sources;
- methods for data-driven optimization through AI and ML;
- tools for information management;
- methods for fairness and transparency in decision making;
- methods for data-driven process model discovery, monitoring and redesign;
- methods for automating integration of machine learning and knowledge based models; and
- techniques for explainable AI based on interpretable data driven models for human decision making.
The work focuses on the interplay of machine learning, optimization, and interpretability. These techniques are integrated in decision making pipelines that facilitate their joint use as well as the joint use of techniques from other research clusters.
Some of our research projects
Data Analytics for Trade Lane Risk Assessments and Control (DARA)
We aim to develop advanced data analytics solutions that can significantly improve current risk assessments and result in further trade…
Integrated Synchromodal Transport System Analysis
ISOLA: support the development of the multimodal transport system in the Netherlands, and by extension in Europe, into a truly synchromodal…
Programmatic Advertising Support System (PASS)
Design a computerized support system for small- and medium-size online publishers to optimize programmatic buying decisions