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About

Pan Yu is a versatile researcher whose work spans tensor networks, machine vision, and surgical robotics. His most cited paper, "Tensor Networks Meet Neural Networks: A Survey and Future Perspectives" (2023, 14 citations), provides a comprehensive overview of how tensor networks—originally developed to overcome the curse of dimensionality in large-scale tensor computations—can be integrated with neural networks for more efficient data modeling. This survey has become a key reference for researchers exploring the intersection of these two powerful frameworks. In parallel, Yu's work on "Tomato Sorting System Based on Machine Vision" (2024, 13 citations) addresses practical agricultural challenges by developing an automated system that improves sorting accuracy and efficiency, reducing reliance on subjective manual processes. His contributions extend to medical robotics, where his paper on "Soft Robots with Cy5" (2024, 5 citations) introduces an innovative imaging technique for intraoperative navigation during laparoscopic gastric surgery, enabling precise tumor localization. Additionally, his research on joint trajectory generation for obstacle avoidance in tight spaces (2023, 2 citations) advances robotic manipulation in constrained environments. With a growing citation record and applications spanning AI, agriculture, and healthcare, Pan Yu demonstrates a remarkable ability to bridge theoretical innovation with real-world impact.