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About

Yuan-Chieh Lo is a researcher at the forefront of intelligent manufacturing, specializing in cyber-physical robotic systems for high-precision grinding and polishing. His work bridges the gap between traditional, expert-dependent manufacturing and fully autonomous, data-driven production. Lo’s major contributions include developing a "zero-tuning" grinding process methodology that eliminates the need for skilled engineers to manually adjust robot programming, significantly enhancing process quality and efficiency. He has also pioneered the application of deep learning for automated defect detection, using Faster R-CNN to identify flaws in grinded and polished workpieces—a critical step toward fully automated quality inspection. Additionally, Lo has advanced the field by creating a normal force estimation model for robotic belt-grinding systems, addressing a long-standing challenge in finishing processes. With his most-cited papers accumulating over 25 citations, Lo’s work is shaping the future of smart factories, where cyber-physical systems and AI converge to make high-risk, labor-intensive manufacturing safer, more consistent, and less reliant on human expertise.