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About

Guoyi Yu is a leading researcher in energy-efficient hardware acceleration for robotics, IoT security, and autonomous systems. His work focuses on designing reconfigurable coprocessors and cryptographic accelerators that balance high performance with minimal area and power consumption—critical for resource-constrained mobile robots and smart sensors. Yu’s most-cited paper (11 citations) introduces a reconfigurable matrix multiplication coprocessor optimized for visual intelligence and autonomous navigation, supporting algorithms like Extended Kalman Filters and reinforcement learning. He has also advanced SLAM for mobile robots with an efficient hardware accelerator for non-linear optimization correlative scan matching (9 citations), and developed a low-computation Sobel edge detector for real-time robot vision (5 citations). In IoT security, Yu’s cryptographic accelerator (9 citations) enables low-cost, high-performance network security for devices like intelligent sensors. His contributions bridge algorithmic complexity and hardware efficiency, making autonomous systems more practical and secure. With a publication record spanning 2021–2022, Yu’s work is foundational for next-generation edge computing in robotics and IoT.