Resilient Urban Networks Lab
We develop computational models to study the resilience of urban complex systems
Research Projects at the RUN Lab
see Google Scholar for up-to-date list of works
Socioeconomic resilience to behavioral changes
How do behavioral shifts (e.g., hybrid work, fare-free bus systems, infrastructure development) reshape our urban activities, social interactions, and the resilience of business ecosystems? We are developing network-based models to understand and predict how behavioral changes spillover to nearby businesses. ​Take a look at our recent work investigating the effects of behavior-based dependency networks on economic resilience!
Cross-city learning of mobility dynamics during disasters
Cities are expected to face increasing unprecedented disasters due to climate change. Can cities learn from other cities’ past experiences to predict urban mobility dynamics in such scenarios? We are developing machine learning models for translating urban network structures (Nature Machine Intelligence), urban land-use and functions (ACM KDD), and mobility patterns (ACM SIGSPATIAL) across cities. This project is funded by the NSF HDBE Program.
Social interactions in urban environments
Rich social interactions are associated with health, economic mobility, and social capital. When, how, and why do social interactions emerge in public spaces? We are working with public agencies to answer these questions by using large-scale behavioral data. Check out our work on understanding experienced segregation after the pandemic (Nature Communications), diverse encounters in social infrastructure (CEUS), and impacts on resilience (Transportation Research Part D).
Designing community-centric EV infrastructure
The United States is investing heavily on EV infrastructure. How can we design EV charging infrastructure networks and behavioral incentives for drivers that benefit the community & local enterprises? We are leveraging causal inference techniques (e.g., synthetic control, RDD) to quantify the economic impacts of EV infrastructure placement from quasi-natural experiments. Collaboration with NovaCHARGE. This project is funded by the NSF SAI Program.
Towards open mobility data science for policy
How can we leverage mobility phone location data to understand population dynamics for policy, such as disaster response and management? We are developing open source toolkits and datasets (Nature Computational Science) -- examples include ​Mobilkit, an open source toolkit for mobility analytics with the World Bank, YJMob100K, an open source mobility dataset with Yahoo Japan, and nation-wide synthetic mobility data with the University of Tokyo (CACAIE).