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Active Research Projects

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.

Recent Publication

cover page of the USE-Lab working paper

Time-varying, people-centric criticality of electricity distribution feeders

Hongrong Yang
Markus Schläpfer

News

June 23, 2026

New paper published in Computers, Environment and Urban Systems

Using optimal transport theory and mobility data from Singapore’s MRT system, we show that urban travel patterns are shaped more by the collective decisions of travelers than by centrally optimized routing, emphasizing the role of self-organization in the design of efficient and people-centric transit systems.

April 07, 2026

Columbia Engineering highlights Nature Communications paper

Our recent paper in Nature Communications on electric vehicle charging and photovoltaic integration in tropical cities was featured by Columbia Engineering. The study shows how decentralized charging strategies can substantially increase the amount of solar energy that cities can integrate while reducing stress on the electrical grid.