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Vision Statement
As a researcher who leverages sensing, computational modelling, data-analytics, reliability, artificial intelligence and engineering domain knowledge to study civil infrastructure systems, my research vision seeks to streamline the assessment of infrastructure systems’ performance over their entire lifespan (i.e., their past, present and future) through a synergistic paradigm for monitoring, interpretation, modelling and assessing infrastructure systems. I envision that I will further enhance circular infrastructure through knowledge circularity that reuses and recycles the extracted engineering knowledge for the analysis, design, construction, operation and management of both existing and next-generation civil infrastructure systems.
I also envision that my applications will span multiple domains, including but not limited to, geotechnical engineering, road infrastructure and energy. This architecture inherently stimulates collaborations across traditionally distinct research domains. Through establishing collaborative research programs that pool collective knowledge and intelligence, my research vision endeavours to address specific challenges individually before I can strategically combine the outcomes to provide a synergistic methodological framework for through-life analysis and management of infrastructure systems.
Beyond data-driven: a synergistic paradigm for achieving knowledge circularity in through-life analysis of geotechnical/civil infrastructure systems
The PAST of an infrastructure system:
This research capitalizes on historical data of infrastructure systems to extract interpretable, self-explanatory and physics-based knowledge of their performance.
The PRESENT of an infrastructure system:
This research develops methodological framework for building model-based cyber-physical infrastructure systems for achieving real-time/near-real-time human machine interactions and timely decision-making.
The FUTURE of an infrastructure system:
This research explore viable integration of engineering knowledge obtained from Past & Present performance data into the conventional reliability & performance-based analysis and design of infrastructure systems for issues spanning safety concerns, emission reduction, resilience against natural disasters, energy efficiency, among others.
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