Computational Simulations for Disaster Risk Management

Faculty of Engineering

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Research project description

As climate change increases the frequency and severity of disasters, proactive planning for post-disaster housing recovery is essential to mitigate long-term social and economic disruption. Computational models can support this planning by simulating potential recovery trajectories, yet many existing approaches are limited by overwhelming data requirements or narrow applicability to past events. Our work focuses on developing novel computational tools to improve how we manage disaster risk. These can include computational simulations using agent-based models or computer vision-based algorithms to study post-disaster recovery in communities.

Fields of research

  • Climate change adaptation
  • Disaster risk reduction
  • Computational models
  • Agent-based and data-driven models

Qualifications and ideal student profile

Prospective graduate student researchers must meet or exceed the minimum admission requirements for the programs connected to this opportunity. Visit the program pages using the links on this page to learn more about minimum admission requirements. In addition to minimum requirements, the research supervisor is looking for the following qualifications and student profile.

  • Required qualifications include a bachelor's degree in a related field (ideally, engineering), coursework in probability and statistics, experience working with data, and above all, an interest in the field of natural hazards engineering, climate change and disaster risk mitigation, and community resilience
  • The ideal candidate will have one or more of the following:
    • (i) experience in the field of disaster risk management
    • (ii) coursework in computational simulation, data analysis, and/or Machine Learning (ML)/Artificial Intelligence (AI)
    • (iii) demonstrable interest in my previous and future work

Faculty researcher and supervisor

Important dates

Computational Simulations for Disaster Risk Management  is an open and ongoing research opportunity. Expressions of interest can be submitted for any term.

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