17:00 PM

ECE Graduate Student Yuqi Li Receives Third Place at DAC

This award-winning demo helps bridge the gap between personal privacy and safety monitoring

Yuqi Li, a graduate student in the Electrical and Computer Engineering Department at the University of Pittsburgh Swanson School of Engineering, impressed hundreds of industry leaders and peers at this year’s Design Automation Conference (DAC)’s University Demo Competition. 

Li’s demo, “FPGA HLS acceleration on real-time fiber-optical-based pattern recognition system,” received third place at the competition, one of the most prestigious and fierce in the nation. 

“This is an extraordinary achievement,” said Kevin Chen, Paul E. Lego professor of electrical and computer engineering at the Swanson School and one of Li’s advisors. “This achievement highlights high levels of innovation and efficiency that Pitt is committed to.” 

Yuqi Li and Team


The project is designed to address the conflict between society's demand for security monitoring and individuals' insistence on preserving personal privacy. 

For it to work, an optical fiber that contains a specific-engraved optical structure is positioned on the ground. As individuals pass through this area, variations in pressure give rise to alterations in the optical structure. Since different people have different physical conditions, like weight and stride length, a trained neural network is used to distinguish changes in optical structural characteristics so it can recognize walking patterns. In addition, to ensure real-time monitoring capabilities, the project integrates HLS (High Level Synthesis) acceleration technology into the FPGA data flow design to effectively manage the massive data load generated by the fiber optic sensing system. This technology serves as a remarkably effective complementary tool for safeguarding critical infrastructure. 

Technology like this can be used in places like nursing homes, where comprehensive resident security monitoring is required. It not only ensures safe monitoring of occupants in private spaces, but it circumvents potential privacy invasions associated with camera surveillance.

“I am delighted that the significance of this project has garnered recognition. Yet, I must admit to a certain apprehension accompanying this award, as I am aware that the project still holds numerous challenges to overcome before it can truly address real-world issues,” Li said. “I am very grateful to my colleagues, Qirui Wang, Jieru Zhao, Kehao Zhao, and Shuda Zhong, who have given me countless help. I would also like to express my deep gratitude to Dr. Kevin Chen and Dr. Peipei Zhou for their meticulous guidance and help during my doctoral study.” 

The demo was funded in part by Leidos, an American defense, aviation, information technology, and biomedical research company.