Research Overview

The AI and Simulation Lab develops AI-powered modeling and simulation methods for understanding human mobility, urban systems, public health, and community resilience.

Our work integrates geospatial artificial intelligence, agent-based modeling, large language models, synthetic populations, and high-performance computing. Explore the six connected research areas below.

Human Mobility Intelligence

Human Mobility Intelligence combines mobility data science, geospatial artificial intelligence, agent-based modeling, and behavioral simulation to understand how people move, conduct activities, and interact across space and time.

Generative Mobility Simulation

Generative Mobility Simulation creates realistic, scalable synthetic populations and mobility traces for locations where representative data are sparse, restricted, or unavailable.

LLM-Enabled Behavioral Simulation

LLM-Enabled Behavioral Simulation investigates how large language models can help specify, generate, and adapt human behavior within transparent simulation environments.

Mobility Anomaly Generation

Mobility Anomaly Generation produces realistic, controllable deviations from normal movement while preserving causal explanations and physical feasibility.

Urban Digital Twins and Transportation

Urban Digital Twins and Transportation research connects human mobility, transit policy, and microscopic traffic simulation in scalable computational environments.

GeoAI for Health and Resilience

GeoAI for Health and Resilience applies spatial analytics and simulation to public health, disasters, climate stress, and unequal access to critical resources.