Jinhua Xu

City University of Hong Kong, Nanjing University of Aeronautics and Astronautics

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About

Jinhua Xu is a pioneering researcher whose work bridges advanced computational intelligence and cutting-edge manufacturing technologies. Their early contributions focused on nonlinear system identification, where they developed adaptive wavelet networks that combine the function approximation power of neural networks—such as multilayer perceptrons and radial basis functions—with the multiresolution capabilities of wavelet transforms. This foundational work, published in 1999 and cited 24 times, established a novel framework for representing complex systems with enhanced accuracy and efficiency. More recently, Xu has made significant strides in additive manufacturing, particularly in the robotic fabrication of continuous fiber composites. Their 2025 study on curved layering and path planning, based on multi-direction slicing, has already garnered 6 citations, reflecting its timely impact on the field. This work addresses critical challenges in composite manufacturing by optimizing fiber orientation and deposition paths, enabling stronger, more complex geometries. Xu’s research trajectory demonstrates a unique ability to integrate theoretical innovations with practical engineering solutions, making their contributions valuable for students and researchers in computational modeling, robotics, and advanced materials.