Riyang is a postdoctoral associate at the Yale School of Public Health specializing in high-resolution ambient air pollution exposure modeling and health impact assessment. His research integrates multisource geospatial big data, including ground monitoring networks, satellite remote sensing, reanalysis products, and chemical transport models, with advanced GeoAI techniques to develop scalable modeling frameworks that generate consistent, spatially explicit exposure estimates. His work focuses particularly on long-term historical pollution trends, extreme exposure events, and health-relevant exposure metrics, enabling improved large-scale epidemiological studies, risk assessment, and policy applications under climate change.
