He works on problems at the intersection of public health, urban analytics, network science, and artificial intelligence. He develops agent-based models known as synthetic information systems, which are large-scale, high fidelity, data-driven simulation models of human populations and infrastructures. These models are used in the study of topics including disease epidemiology, environmental effects on health, and disaster response. His work has won several awards, including first place in the 2016 NIEHS Climate Change and Environmental Exposures Challenge.