Zhan Ling
Papers
1
Total Citations
20
H-Index
1
About
Zhan Ling is an emerging researcher specializing in computer vision, sensor simulation, and robotics perception. Their most notable work addresses one of the fundamental challenges in modern robotics and computer vision: bridging the gap between simulated and real-world optical sensing environments. In their highly regarded 2023 paper, "Close the Optical Sensing Domain Gap by Physics-Grounded Active Stereo Sensor Simulation," Ling and collaborators developed a fully physics-grounded simulation pipeline for active stereovision depth sensors — technology widely adopted across both academic research and industrial applications. By drawing inspiration from the underlying physical mechanisms of these sensors, the work incorporates material acquisition and ray-tracing techniques to produce remarkably realistic sensor simulations, enabling more reliable sim-to-real transfer in robotics and perception systems. This contribution, which has already garnered 20 citations since its publication, demonstrates Ling's ability to connect theoretical physical modeling with practical engineering challenges. Their research holds particular significance for the robotics and autonomous systems communities, where high-fidelity sensor simulation is critical for training and validating perception algorithms before real-world deployment.
Research Focus
Key Achievements
Top Papers
- 1