Research Interests:​​

  1. Resilience of Urban Coupled Socio-Physical Systems

    • Inferring the inter-dependencies between urban social and physical systems, and how they affect the resilience of cities.

    • Prescriptive modeling to guide policies for resilient and sustainable urban growth.

  2. Location Big Data Analytics for Disaster Response

    • Analysis of population displacement and recovery after shocks (e.g. disasters, pandemics) using mobile phone location data, social media data, and satellite imagery.

    • Causal impact estimation of shocks on business performances using mobility data.

  3. Artificial Intelligence for Urban Science

    • Deep learning-based methods to understand urban functionality, hierarchical structures, and similarities between cities using dynamic trajectory data.

Selected Works:​​

Understanding Post-Disaster Population Recovery Patterns
Yabe, T., Tsubouchi, K., Fujiwara, N., Sekimoto, Y., Ukkusuri, S.V.
Journal of the Royal Society Interface (2020)
Quantifying the Economic Impact of Extreme Shocks on Businesses using Human Mobility Data: a Bayesian Causal Inference Approach
Yabe, T., Zhang, Y., & Ukkusuri, S.V.
EPJ Data Science (2020)
Post-Disaster Analytics using Mobile Phone Data: A case study of the Puebla earthquake
Yabe, T., Jones, N. K., Lozano-Gracia, N., Khan, M. F., Ukkusuri, S. V., Fraiberger, S. & Montford , A.
KDD Workshop on Data-Driven Humanitarian Mapping (2021)