Robust Inference and Uncertainty Quantification for Data-Driven Decision Making

Machine learning models have become essential tools for decision-making in critical sectors such as healthcare, public policy, and finance. However, their practical application faces two major challenges: selection bias in the data and the proper quantification of uncertainty.