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About

Huangyi Qu is a pioneering researcher at the intersection of advanced manufacturing, artificial intelligence, and immersive simulation. Their primary research areas include intelligent welding process monitoring, digital twin technology, and AI-augmented additive manufacturing. Qu’s most impactful contribution is the development of a digital twin approach for predicting weld penetration in TIG welding, a critical challenge in manufacturing where real-time sensing limitations hinder quality control. By integrating a dual ellipsoid heat source model, their work has achieved 11 citations and laid the foundation for improved semantic segmentation methods that enhance prediction accuracy. Qu also contributed to the visionary "Roadmap on Artificial Intelligence‐Augmented Additive Manufacturing," which outlines how AI can drive autonomous, adaptive fabrication—a work already garnering 3 citations. Additionally, their innovation extends to safety training with "RobotFire," a multisensory VR simulator that uses robot-assisted smoke and temperature simulation for firefighter education. With a growing citation impact across these diverse fields, Huangyi Qu is establishing themselves as a key figure in smart manufacturing and human-robot interaction, bridging theoretical AI with practical, real-world applications.