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About

Jinzheng Guang is a rising researcher at the forefront of 3D perception and biometrics, with a primary focus on LiDAR-based pedestrian detection for autonomous driving and intelligent robotics. Their work directly tackles the formidable challenges of sparse point cloud data and highly deformable human postures. Guang’s major contributions include the development of **RPEA** (Residual Path Network with Efficient Attention), a novel architecture that achieved 10 citations in 2024 by significantly improving detection accuracy in complex environments. They further advanced the field with **DCCLA** (Dense Cross Connections with Linear Attention), which enhances feature extraction while maintaining computational efficiency—a critical balance for real-time autonomous systems. Demonstrating remarkable versatility, Guang has also innovated in acoustic biometrics with **DFSC-DA**, a dominant frequency segmented conformer that applies domain adaptation to footstep-based person identification, achieving 3 citations in 2025. Their work bridges the gap between robust 3D perception and non-visual identification, showcasing a unique ability to solve sparse-data problems across modalities. With a growing citation impact and a clear trajectory toward safer autonomous systems, Jinzheng Guang is a name to watch in the evolution of intelligent perception.