Presentations will cover methodological priorities for using residential history in population health research, as well as causal inference frameworks informed by historical and contextual factors that shape residential relocation patterns and place-based exposures; novel approaches to tracking neighborhood attributes over time; protocols for collecting and integrating residential history information into cohort studies; and emerging trends in spatial and life-course epidemiology, incorporating advances in machine learning, artificial intelligence, and geospatial analytic techniques. Finally, the symposium will highlight methodological innovations that consider residential relocation as a quasi-experiment to understand how changes in neighborhood environments impact health outcomes. Collectively, the session will foster a rich discussion of the opportunities and challenges in incorporating residential history data into epidemiologic research, highlighting how this information can advance our understanding of place and health, and setting priorities for future research.