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About

Shuai Teng is a researcher whose work bridges the critical fields of intelligent infrastructure inspection and bionic robotics. His most impactful contributions lie in the development of AI-driven systems for structural health assessment, particularly for underwater and sewer infrastructure. His highly cited 2024 review on intelligent detection of underwater structures (65 citations) and his 2023 paper on real-time sewer defect detection using an optimized YOLO network with transfer learning and channel pruning (53 citations) demonstrate his leadership in applying deep learning to automate and enhance the safety of civil engineering inspections. Beyond infrastructure, Teng has made notable strides in bionic robotics, drawing inspiration from animal locomotion. His work on the bionic goat quadruped robot—detailing its mechanical design and gait planning for improved stability on slopes—has been published in multiple papers (2019, 2020) and explores how head movement adjustments affect balance in agricultural robots. This dual focus on practical AI for asset management and bio-inspired mechanical design showcases a versatile engineer addressing real-world challenges from the seabed to the farm field.