Chang Li is a PhD student in Geography at the University of Nebraska–Lincoln, where he also teaches as a graduate teaching assistant for GEOG 155. His research sits at the intersection of remote sensing, GeoAI, and hazard mitigation planning, with a regional focus on flooding in the Great Plains. His dissertation develops a Sentinel-2 based flood inundation mapping workflow for the March 2019 Nebraska floods, builds a statewide critical infrastructure database classified into the FEMA Community Lifelines taxonomy using a hybrid rule-based and large language model pipeline, and couples the two to quantify event-based infrastructure flood exposure. He is broadly interested in how earth observation and machine learning can make state and county hazard mitigation plans more evidence-driven. 

Chang holds an MSc in Geospatial Sciences from University College London and a BA in Cartography and Geographic Information Systems from the University of Wisconsin–Madison, following earlier undergraduate training in accounting and finance in the UK and China. In summer 2025 and 2026 he was a research intern at FM, working on DEM standardization and cloud migration for catastrophe modeling.