Department of Civil and Construction Engineering · Taiwan TechData reference: July 2026
jschou@mail.ntust.edu.tw
Original intelligent optimization × Civil engineering AI × Sustainability and public value

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AI and Metaheuristics for Engineering Resources

The legacy site's curated resources for artificial intelligence, data science, metaheuristics, software, datasets, and engineering informatics.

Integration note: This page preserves the original names, dates, and source languages for accurate archival reference. Where a summary metric differs, the July 28, 2026 print dossier and the current overview pages take precedence.

AI-Inspired Metaheuristic Algorithms for Intelligent Engineering Optimization

Advancing next-generation engineering solutions through creative computational intelligence, innovative algorithm design, and data-driven optimization for smart, resilient, and adaptive infrastructure systems.

My research program focuses on the development of AI-inspired metaheuristic algorithms and their application to complex engineering optimization problems. Drawing inspiration from nature, human behavior, cultural practices, and scientific inquiry, we design novel optimization frameworks—such as JSO, FBI, PWO, ATO, AEIO, ED, SAPSO, AAA, and others—that advance both the theoretical foundations and practical capabilities of computational intelligence. These algorithms empower innovative solutions in structural design, civil infrastructure systems, geotechnical assessment, environmental risk modeling, and automated engineering decision making. Through the integration of large language models, computer vision, machine learning, and metaheuristic optimization, our work aims to enhance engineering performance, enable data-driven planning and design, and contribute to the next generation of smart, resilient, and adaptive engineering systems.