Data-driven Optimization in Operations Research
Data-driven decision-making requires domain experts to manage data, tune models, and personalize decisions, all of which is laborious and can lead to delays in downstream operations. This research introduces new machine learning-based techniques for automated decision-making that can reduce this human labor and improve the quality of operational services.
Relevant publications
- Learning to optimize contextually constrained problems for real-time decision generation Management Science 2023 arXiv