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About

Yanguo Jing is a researcher whose work spans climate science, cybersecurity, and intelligent manufacturing, demonstrating a remarkable breadth of expertise. His early contributions focused on atmospheric remote sensing, notably developing a method for retrieving aerosol optical depth over snow-covered surfaces using AATSR satellite data—a critical advancement for understanding aerosol impacts on Arctic climate and snow albedo, with 27 citations. More recently, Jing has pioneered the application of Digital Twin technology in manufacturing, authoring a highly cited 2024 paper (23 citations) on leveraging Digital Twins to enhance cybersecurity in cyber–physical production systems, addressing vulnerabilities in increasingly connected intelligent factories. His work also includes innovative approaches to human-robot collaboration, with a generic and modularized Digital Twin framework (2022) that enables safer, more flexible manufacturing. Jing has further advanced learning from demonstration techniques through improved Gaussian mixture models (2025, 17 citations), and explored autonomous exploration with limited-field-of-view sensors for underwater and aerial vehicles (2025). This diverse portfolio—from Arctic aerosols to industrial cybersecurity—underscores Jing’s ability to tackle complex, cross-disciplinary challenges, making his research highly relevant to students and professionals in climate science, robotics, and smart manufacturing.