Jingxi Li

Papers

Total Citations

163

H-Index

About

Jingxi Li is a pioneering researcher at the intersection of computational imaging, deep learning, and all-optical information processing. Her work fundamentally reimagines how we capture and reconstruct visual information, moving beyond traditional digital computation toward ultrafast, hardware-based solutions. Her most cited work, “Computational imaging without a computer: seeing through random diffusers at the speed of light” (2022, 163 citations), demonstrates a breakthrough approach that eliminates the need for electronic post-processing. By integrating deep learning principles directly into optical systems, Li’s method reconstructs images obscured by random diffusers instantaneously—at the speed of light—achieving what previously required intensive computer algorithms. This paradigm-shifting contribution has profound implications for real-time imaging in scattering media, such as biomedical microscopy, autonomous navigation, and defense. Li’s research exemplifies the emerging field of “optical neural networks,” where physical systems themselves perform computation. Her work has garnered significant attention for its elegance and practicality, positioning her as a leading voice in next-generation imaging. For students and researchers, Li’s trajectory offers a compelling vision of how merging optics with machine learning can bypass traditional computational bottlenecks, opening new frontiers in high-speed, low-latency visual sensing.