India faces escalating risks from hazards such as heat waves, drought, flooding, air pollution, and power outages—threats that affect communities variably densely populated landscape. Despite growing exposure, little is known about how these risks are perceived at the individual or district level. During I-GUIDE's Summer School in August 2025, our group used artificial intelligence and machine learning to build individual-level models of public risk perceptions for the first time in India. These models integrated national survey data with climate exposure and socio-demographic variables to predict perceptions of various hazard and weather-related threats. Ultimately, the results were fed into multilevel regression with poststratification (MRP) models to produce district-level maps of risk perception across the country.