Simon Su

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About

Simon Su is a leading researcher in real-time 3D perception for autonomous systems, with a focus on efficient LiDAR-based object detection. His most notable contribution is the development of **StrObe**, a streaming object detection framework that processes raw LiDAR packets directly—bypassing the traditional, computationally expensive step of assembling full point clouds. This innovation enables robots and autonomous vehicles to detect objects with dramatically lower latency, a critical advantage for safety-critical applications. The work, published in 2020, has garnered 8 citations and is recognized for rethinking the conventional perception pipeline. Su’s research addresses the unique challenges of rolling shutter LiDARs, which are widely used in modern robotics due to their rich geometrical data. By operating on streaming packet data, StrObe achieves real-time performance without sacrificing accuracy, setting a new standard for efficient 3D perception. His contributions are particularly influential for students and engineers working on embedded systems, autonomous navigation, and high-speed robotics, where every millisecond of delay matters.