Dissertation Announcement: Quinn Lanners

Advisor(s): Cynthia Rudin and David Page Dissertation Title: Domain-Guided Machine Learning: Trustworthy Methods for Causal Inference and Rare Event Prediction Abstract: As machine learning becomes increasingly capable, it is being applied in high-stakes domains, such as healthcare, public policy, and criminal justice. My research develops machine learning-aided approaches for these settings that center domain expertise throughout the analysis pipeline. This goal is pursued across three problem areas: (i) observational causal inference, (ii) causal inference via data fusion, and (iii) rare event prediction. By actively incorporating the insights and experience of domain experts, this work aims to harness the strengths of modern machine learning while promoting interpretability, robustness, and trust in the results.