Zonglin Meng

University of California, Los Angeles, University of Wisconsin–Madison

Papers

Total Citations

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About

Zonglin Meng is a pioneering researcher at the intersection of cyber-physical-social systems (CPSS) and natural hazard resilience. His work centers on two transformative areas: the digital evolution of the oil and gas industry and advanced flood risk assessment using artificial intelligence. In his highly cited 2024 paper, "A Paradigm Shift for Modeling and Operation of Oil and Gas," Meng critiques the limitations of Industry 4.0’s efficiency-driven approach, proposing a shift toward Industry 5.0 within CPSS that integrates societal and human-centric considerations—a forward-looking framework that has already garnered 22 citations. Complementing this, his 2019 work on "Flood Depth Estimation from Web Images" (21 citations) introduces a novel, data-driven method for rapid post-disaster damage assessment, leveraging publicly available imagery to estimate flood depths without traditional sensor networks. This approach offers a scalable, cost-effective solution for urban resilience planning. Meng’s contributions bridge critical infrastructure modernization with disaster response, demonstrating how AI and systems thinking can address both industrial efficiency and societal safety. His research is essential reading for scholars exploring sustainable digital transformation and climate adaptation technologies.