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)
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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)
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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.
World Bank Working Papers (forthcoming)
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