Yudong Weng
Papers
1
Total Citations
23
H-Index
1
About
Yudong Weng is a researcher advancing the frontier of computational imaging, with a focus on non-line-of-sight (NLOS) imaging and its practical applications in autonomous vehicles, robotic vision, and biomedical diagnostics. His most cited work, "Accurate but fragile passive non-line-of-sight recognition" (2021, 23 citations), introduces a novel framework that prioritizes recognition over reconstruction for classifying hidden objects—a paradigm shift that enhances efficiency in real-world scenarios where full image recovery is unnecessary. By demonstrating that passive NLOS systems can achieve high accuracy while remaining sensitive to environmental perturbations, Weng’s research bridges the gap between theoretical imaging models and robust, deployable systems. His contributions underscore a deep understanding of inverse problems and optical physics, offering a pathway to safer autonomous navigation and non-invasive medical imaging. With his work already shaping discussions on the fragility and potential of passive NLOS techniques, Weng stands out as a rising voice in computational optics, inspiring future explorations into how machines perceive the unseen.
Research Focus
Key Achievements
Top Papers
- 1Accurate but fragile passive non-line-of-sight recognition23 citations · 2021