W3 Seminar – Urban digital twins: An emerging computational framework for making sense of cities

Details

Speaker:
Changjie Chen, Ph.D., Assistant Scientist, Florida Institute for Built Environment Resilience, UF

Abstract:
Cities are complex systems in which physical structures, natural processes, social relations, and human activities coexist and interact across scales. While these interdependencies have long defined urban life, recent advances in data availability, computation, and modeling have dramatically expanded our capacity to represent, integrate, and reason about urban systems. This talk introduces urban digital twins as an emerging computational framework for making sense of cities, providing a means of cultivating integrative knowledge by relating heterogeneous data, models, and system architectures to support informed decision-making about urban futures.

The talk examines urban digital twins as computational infrastructures that shape how urban processes are represented, coupled, and explored. It draws primarily on case studies from Florida, where rapid population growth, sea-level rise, and climate-driven risk have positioned the Florida Digital Twin as a living laboratory for methodological and technical innovation. Examples include regionalization methods for cross-scale data harmonization, applications to coastal vulnerability and adaptation planning, and AI-powered 3D city modeling. The talk also considers emerging extensions that incorporate agentic reasoning within digital twins, reframing computational inquiry around how cities can better support human life.

Bio:
Dr. Changjie Chen is a computational urbanist studying the spatial structure and functional dynamics of cities, with a focus on building scalable and intelligent urban digital twins for modeling, simulation, and planning decision support. His work integrates geographic information systems (GIS), remote sensing, spatial econometrics, artificial intelligence (AI), and high-performance computing (HPC) to fuse large-scale, multi-sector urban data with real-time sensor streams into high-fidelity representations of cities across space and time. Leveraging cloud-based data infrastructures, 3D geospatial data, and smart city ontologies, he develops generative AI pipelines that rapidly reconstruct immersive cityscapes and agentic AI systems that autonomously reason about urban complexity, enabling scenario testing, agent-based experimentation, and the simulation of current and future urban conditions.