Yu Cao

Hunan University, Wenzhou University, Zhejiang Lab

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About

Yu Cao is a versatile researcher whose work spans several cutting-edge technological domains, including point cloud processing, flexible sensing technologies, and optofluidic systems. Among his most recognized contributions is the development of FEC (Fast Euclidean Clustering), a highly efficient algorithm for point cloud segmentation published in 2022, which has garnered 71 citations and addresses a critical challenge in autonomous vehicles, mobile robotics, and remote sensing — the efficient processing of sparse, unstructured 3D data. This work has positioned Cao as a meaningful contributor to the rapidly evolving field of autonomous systems and environmental perception. Beyond computational methods, Cao has demonstrated a strong interest in hardware innovation, developing inkless flexible sensors via laser direct writing — a promising advancement for wearable health monitoring and electronic skin applications. His more recent work explores opto-thermomechanical microfluidics, combining optical trapping with photothermal convection for multiscale particle manipulation on integrated optofluidic chips. Together, these contributions reflect a researcher with a broad interdisciplinary vision, capable of bridging algorithm design, materials engineering, and photonic systems to address real-world technological challenges.