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About

Yihai Fang is a pioneering researcher at the intersection of robotics, automation, and civil engineering, whose work is transforming how we think about construction safety and efficiency. His primary research areas include human-robot collaboration (HRC) in construction, autonomous mobile crane safety, and robotic structural assembly. Fang’s most significant contribution is the development of a physics-informed neural network (PINN) for predicting load sway in travelling autonomous mobile cranes—a critical safety innovation that addresses the risks of instability and collision during crane operations. This work, published in 2025, has already garnered 10 citations for its novel approach to overcoming the inefficiency and inaccuracy of traditional prediction methods. His 2021 paper in the *Proceedings of the 38th International Symposium on Automation and Robotics in Construction (ISARC)* stands as his most cited work with 28 citations, reflecting his leadership in the field. Fang has also advanced task planning for human-robot collaboration in structure assembly, proposing systematic approaches to tackle labor shortages and low productivity, and has investigated positional inaccuracies in robotic construction of load-carrying structures. His research is not only technically rigorous but also practically impactful, directly addressing real-world challenges in construction safety and automation.