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About

Enshen Zhu is a rising researcher at the forefront of digital twin technology and human–robot collaboration (HRC). His work centers on creating intelligent, synchronized digital replicas of physical robotic systems to enable remote monitoring, control, and trust-based interaction. Zhu’s most cited paper, “Building a cloud-based digital twin for remote monitoring and control of a robotic assembly system” (2023, 20 citations), establishes a foundational framework for integrating cloud computing with real-time robotic oversight. He further advances this field by developing computer vision-based synchronization evaluation methods, notably using YOLOv8 for precise alignment between physical and digital systems (2024, 12 citations). A particularly innovative contribution is his “novel digital twins-driven mutual trust framework for human–robot collaborations” (2025, 11 citations), which addresses a critical gap in HRC research: while most studies focus solely on human trust in robots, Zhu explores how human uncertainties and behaviors can disrupt collaborative trust dynamics. His work has significant implications for manufacturing, Industry 4.0, and autonomous systems, offering practical solutions for safer, more reliable human–robot teamwork. With a growing citation record and a clear trajectory toward impactful, interdisciplinary research, Zhu is establishing himself as a key voice in the future of smart manufacturing.