Hao Tang

Hunan University, Hefei University of Technology

Papers

Total Citations

171

H-Index

About

Hao Tang is a versatile researcher whose work spans computer vision, structural health monitoring, robotics, and human-machine systems. His most influential contribution, a comprehensive 2023 review on computer vision-based bridge inspection and monitoring, has rapidly garnered 128 citations, underscoring its significance to the civil engineering and infrastructure communities. In this work, Tang synthesized cutting-edge CV methodologies — valued for their low-cost, non-contact, and remote capabilities — that are transforming how engineers assess the safety and integrity of bridge structures worldwide. Beyond structural monitoring, Tang has demonstrated strong expertise in advanced control systems for bioinspired robotics. His 2020 work on discrete-time steering control for robotic fish, which has earned 42 citations, introduced a novel data-assisted dynamic modeling approach combined with a super-twisting-like algorithm, advancing precision control in underwater robotic platforms. More recently, Tang has extended his research into human-robot collaboration, developing deep reinforcement learning-based hierarchical decision frameworks for human-exoskeleton packaging systems, reflecting his forward-looking interest in intelligent automation and assistive technologies. Collectively, his body of work illustrates a researcher who bridges structural engineering, robotics, and artificial intelligence with both depth and breadth.