Intelligent Disaster Resilience Group

Where your journey begins

Intelligence

Machine learning and deep learning algorithms are actively introduced and integrated with structural reliability methods and theories of mechanics to understand the latent patterns behind random variables.

Disaster

The impact of natural and man-made hazards on civil infrastructural systems is investigated. The influence of climate change on natural disasters is also examined.

Resilience

Resilience is introduced to understand the holistic capability of structural systems under disasters. Structural design and assessment are carried out in terms of resilience.

My research group has focused on developing advanced resilience analysis frameworks and assessing the resilience performance of complex structural systems. By integrating various machine learning and deep learning algorithms with structural mechanics and reliability theories, we not only efficiently assess the performance of structural systems but also effectively understand the behavior of civil systems under various hazards such as earthquakes, wind, and multi-hazards. Further details on the research interests of our group can be found on the Research Page.

We look for passionate students who are committed to assessing the resilience performance of structural systems under natural/man-made hazards.

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