Speaker
Description
The increasing frequency and complexity of natural hazards require civil engineering (CE) education to place a stronger and more explicit emphasis on disaster risk reduction (DRR). At De La Salle University in Manila, Philippines, a graduate seminar course titled Disaster Risk Reduction and Infrastructure Development (DRRID) has been introduced to enhance the awareness of civil engineering professionals and researchers regarding the role of various CE specializations in advancing disaster risk reduction and strengthening the resilience of infrastructure systems in the built environment. Teaching modules were designed and delivered in a hybrid classroom environment. A key feature of the modules is the systematic alignment of civil engineering specialization-specific tasks with the four priorities of the Sendai Framework for Disaster Risk Reduction: understanding disaster risk, strengthening disaster risk governance, investing in disaster risk reduction for resilience, and enhancing disaster preparedness.
One key component of the course is the integration of Artificial Intelligence (AI) and Information and Communication Technology (ICT) as emerging tools for research in CE–DRRID. One of the teaching and learning modules introduces applications of AI/ICT in areas such as hazard and risk modeling, image processing and computer vision, structural damage detection and health monitoring, and decision-support systems. To deepen their understanding of these technologies, students are required to complete an individual Review of Related Literature (RRL) assignment that examines at least five journal articles focusing on a specific AI tool, software platform, or algorithm and its application to civil engineering and disaster risk reduction.
As a culminating requirement, students develop and present a concept proposal integrating civil engineering, DRR, and AI/ICT in DRRID Forum. The proposals must address a CE specialization, align with at least one priority of the Sendai Framework for Disaster Risk Reduction, and demonstrate the potential use of AI or ICT tools for analysis, simulation, or decision-making. Selected highlights from these proposals illustrate how AI/ICT integration can broaden research perspectives while reinforcing the central role of engineering judgment in resilient infrastructure development.
