Di Wang

Di Wang is a One-U Responsible Artificial Intelligence (AI) Postdoctoral Fellow at University of Utah. Wang's research sits at the intersection of artificial intelligence, disaster recovery, and community resilience. As climate-related hazards grow more frequent and severe, Wang studies what happens long after the emergency itself, focusing on the complex, extended phases of recovery that shape whether communities truly rebuild. 

Most AI work in this space stops at immediate response—but recovery is where Wang focuses. He builds models that draw on a wide range of signals, including social media posts, geolocated imagery, mobility patterns, field observations, and official disaster reports, to piece together how communities move through recovery over time. Wang aims to identify where progress is happening, where it stalls, and where gaps in aid leave certain populations behind.

He is particularly interested in what recovery looks like at the ground level: how households adapt, how housing stock shifts, and how local businesses find their footing again after disaster strikes. These micro-level dynamics reveal important connections between individual decisions and broader patterns of resilience, and they raise urgent questions about why recovery unfolds so differently across communities.

Ultimately, Wang wants to build AI tools that are not just technically sound but genuinely useful—to researchers, to recovery practitioners, and to the communities navigating these challenges firsthand. Grounded in responsible AI principles, Wang's work aims to support more transparent, equitable, and informed decision-making in the wake of disaster.