Shaojie Xu

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About

Shaojie Xu is a researcher at the forefront of energy-efficient computer vision and embedded systems, with a primary focus on developing ultra-low-power smart cameras for always-on applications. His major contributions lie in pioneering compressed domain gesture detection, a technique that dramatically reduces energy consumption by extracting gesture features directly from compressed image sensor measurements—such as block averages and linear combinations—rather than processing full-resolution images. This innovation enables continuous, light-powered operation, making his systems ideal for battery-free or energy-harvesting environments. Xu’s most-cited works, including "A Light-Powered Smart Camera With Compressed Domain Gesture Detection" (2017, 11 citations) and its earlier 2016 version (9 citations), have laid the groundwork for sustainable, always-on visual sensing. His research directly addresses the critical challenge of balancing computational accuracy with extreme power efficiency, impacting fields like IoT, wearable devices, and ambient intelligence. By demonstrating that robust gesture recognition can be achieved with minimal energy, Xu has established himself as a key contributor to the next generation of autonomous, self-powered smart cameras.