Mingyue Shao

Agricultural Information Institute, Xi'an University of Technology

Papers

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About

Dr. Mingyue Shao is a rising interdisciplinary researcher whose work bridges agricultural technology and advanced robotics. Her primary research areas include deep learning for precision agriculture and the dynamic modeling of robotic systems. Dr. Shao’s most significant contribution lies in developing a lightweight, real-time detection model for cotton diseases, designed specifically for resource-constrained devices in natural environments. This work, published in 2024 and already garnering 20 citations, addresses a critical challenge in crop management by enabling rapid, on-site disease identification to protect cotton quality and yield. In parallel, Dr. Shao has advanced the field of robotics through a 2024 study on flexible-joint robots with clearance, employing nonlinear spring-damping and Coulomb models to analyze complex dynamic coupling effects. This research, with 5 citations, provides essential insights for improving robotic precision and reliability. By tackling practical problems in both agriculture and automation, Dr. Shao demonstrates a commitment to developing deployable, impactful technologies. Her work is particularly relevant for students and researchers interested in edge AI, agricultural informatics, and the mechanics of flexible robotic systems.