Predicting mobility flows with urban science and artificial intelligence
Human mobility is not only at the heart of the economic functioning of cities, but it also shapes the demand for infrastructure services. Our goal is to understand and predict people's city-wide mobility patterns and how they affect and are affected by changes in urban infrastructures. To achieve this goal, we combine urban science with artificial intelligence.
Mobility-informed infrastructure planning
The demand for infrastructure like transportation, energy, and water highly depends on the spatial and temporal presence of people. Our research uses high-resolution, dynamic mobility flow predictions to improve infrastructure demand forecasts - particularly for energy systems. This enables both real-time operational support and long-term planning, particularly under stress conditions such as extreme heat.
Urban intensification and infrastructure efficiency
We develop a deep, scientific understanding of how people make use of urban space and use these insights to make infrastructures more efficient and resilient.
Heat exposure mitigation
Extreme heat is the most imminent climate threat facing New Yorkers, contributing to over 500 deaths annually. To assess and mitigate urban heat in public spaces and active mobility infrastructure, our lab has developed a fine-grained urban climate model for NYC.