Ziyang Hong

Papers

Total Citations

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About

Ziyang Hong is a robotics and autonomous systems researcher whose work centers on robust perception, localization, and mapping for mobile robots and autonomous vehicles. His most significant contribution is RadarSLAM, a Simultaneous Localization and Mapping system specifically engineered to overcome the critical limitations of camera and LiDAR-based approaches under challenging illumination and adverse weather conditions — circumstances that routinely degrade conventional sensor data. Published across both 2021 and 2022, this work has accumulated over 80 citations combined, reflecting strong community recognition of its practical importance for long-term autonomous navigation in real-world environments. Beyond radar-based SLAM, Hong has also explored LiDAR data representation through his CURL framework, which proposes a continuous, ultra-compact encoding of point cloud data — an innovative response to the storage and density challenges posed by high-resolution LiDAR sensors. Together, these contributions position Hong as a researcher actively bridging the gap between sensor limitations and reliable robotic autonomy, with a particular emphasis on making perception systems resilient enough for deployment outside controlled laboratory conditions. His work will be of keen interest to students studying autonomous driving, field robotics, and sensor fusion.