Using AI to Build Smarter, More Resilient Cities
Communities need better tools to understand risk, plan for uncertainty, and respond in ways that are fair and effective. Through a National Science Foundation–funded research collaboration, CAPPA is applying artificial intelligence and integrated urban data to help cities model complex systems, anticipate disruptions, and design more resilient planning strategies grounded in both infrastructure performance and community needs.
UTA’s College of Architecture, Planning, and Public Affairs has been awarded a $153,241 subaward as part of a multi‑institutional research initiative led by Prairie View A&M University and supported by the National Science Foundation. The project, Excellence in Research: Implementing Urban Digital Twins with Responsible Foundation AI for Community Resilience, brings together interdisciplinary expertise in planning, architecture, engineering, and data science to develop urban digital twins—AI‑enabled digital representations of cities that integrate physical, environmental, and social data to inform planning and decision‑making.
UTA’s research team will lead efforts focused on connecting community‑level data with physical and environmental systems, ensuring that advanced AI models account for real‑world conditions and social dynamics alongside technical performance.
“Urban digital twins become truly useful when they reflect how people, infrastructure, and environmental systems interact in real cities,” said Dr. Wei Zhai, Principal Investigator for UTA and Associate Professor in the Department of Public Affairs & Planning at UTA. “Our work emphasizes responsible AI approaches that help planners and decision‑makers understand not only where risks exist, but how those risks affect communities and inform fair, practical responses.”
Dean of CAPPA Dr. Ming‑Han Li highlighted the broader significance of the initiative for applied research and public‑interest planning.
“This research reflects CAPPA’s commitment to translating advanced technologies into tools that support better planning and stronger communities,” Li said. “By integrating social context into AI‑driven urban models, this work helps ensure that planning decisions are informed, grounded, and responsive to real community conditions.”
According to Dr. Zhai, the project is also designed to support future collaboration and investment.
“This NSF‑funded partnership allows us to test scalable methods that can be applied in collaboration with public agencies, regional partners, and industry,” Zhai said. “It lays important groundwork for future research, applied pilot projects, and additional external funding focused on urban resilience and responsible data use.”
The initiative aligns with NSF priorities around trustworthy artificial intelligence, interdisciplinary research, and the translation of foundational research into practice. Project outcomes are expected to contribute new planning frameworks, replicable urban analytics methods, and research insights relevant to cities facing climate‑driven and systemic challenges.
The project period runs from September 2025 through August 2027, with results shared through peer‑reviewed publications, technical reports, and collaborative research forums.