Papers
3
Total Citations
9
H-Index
2
About
Shaoyu Sun is a leading researcher at the forefront of 3D perception and autonomous systems, with a primary focus on point cloud processing, multi-object tracking, and trajectory prediction. His work directly addresses critical challenges in autonomous driving, robotics, and intelligent transportation. Sun’s major contributions include the development of a novel point cloud object recognition method using histograms of dual deviation angle features, which enhances 3D perception accuracy for LiDAR-based applications. He also pioneered an intra-frame graph structure and inter-frame bipartite graph matching approach for multi-object tracking, incorporating ReID-based occlusion resilience to maintain identity consistency in complex environments. Additionally, Sun introduced a heterogeneous multi-agent risk-aware graph encoder with a continuous parameterized decoder for trajectory prediction, specifically designed to mitigate collision risks at intersections. His research has garnered increasing attention, with his most cited work accumulating 5 citations since 2023, reflecting its growing impact in the field. Sun’s innovative graph-based and risk-aware methodologies are shaping the next generation of safe, reliable autonomous navigation systems.
Research Focus
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Top Papers
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