Yang Hong-xi

Chinese Academy of Sciences, Monash University

Papers

Total Citations

H-Index

About

Yang Hong-xi is a pioneering researcher at the intersection of advanced manufacturing and artificial intelligence, with a primary focus on intelligent robotics for aerospace applications. His most significant contribution lies in developing adaptive, AI-driven systems for automated machining of complex aerospace components, particularly those with large-curvature surfaces. His landmark 2025 paper on "Adaptive PCA-Based Normal Estimation for Automatic Drilling System" introduces a novel method that enables manufacturing robots to autonomously interpret and adjust to intricate geometries in real time, a critical advancement for Industry 5.0. This work, already garnering 4 citations, addresses a fundamental challenge in high-precision aerospace assembly. Demonstrating remarkable interdisciplinary breadth, Hong-xi has also ventured into medical AI, co-authoring "Deep Learning: A Primer for Neurosurgeons" (2024), which bridges the gap between cutting-edge computational methods and clinical practice. His research is characterized by its practical impact, directly enhancing the autonomy and precision of manufacturing systems while exploring transformative applications of deep learning across engineering and medicine.