Liang Pang

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About

Liang Pang is a rising researcher at the forefront of 3D computer vision and neural scene representation. His primary research focus lies in advancing Neural Radiance Fields (NeRFs) and their application to novel sensing modalities, particularly thermal imaging. Pang’s most notable contribution is the development of **Thermal-NeRF**, a pioneering framework that extends the capabilities of NeRFs from visible-light cameras to infrared sensors. This work, published in 2024 with 16 citations, addresses a critical gap in the field by enabling high-fidelity 3D geometry and environmental appearance reconstruction from thermal data—a challenging domain due to the lack of texture and unique physical properties of infrared radiation. By demonstrating that NeRFs can effectively encode detailed 3D structures from thermal inputs, Pang has opened new avenues for applications in nighttime surveillance, autonomous navigation, and non-destructive testing. His research bridges the gap between traditional explicit 3D representations and neural implicit methods, offering a promising alternative for robust scene understanding in low-visibility conditions. As an early-career scholar, Liang Pang is already establishing himself as a key innovator in multimodal neural rendering, with his work poised to influence both academic research and practical deployment in robotics and computer vision.