Profile
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🎓 Early Academic Pursuits
Dr. Yong Li’s academic journey showcases a strong foundation in engineering and traffic systems. He began his higher education at Beijing Union University, earning a Bachelor’s degree in Electrical Engineering and Automation between 2011 and 2015. This foundational training set the stage for his specialized focus in traffic and control systems.
Continuing on an ambitious academic path, he pursued both his Master’s (2015–2017) and Ph.D. (2017–2021) degrees in Traffic Information Engineering and Control at Beijing Jiaotong University, one of China’s top institutions in transportation sciences. His graduate studies equipped him with in-depth knowledge in traffic monitoring, signal processing, and system optimization—areas that would become central to his later research.
👨‍🏫 Professional Endeavors
After completing his doctorate, Dr. Li immediately immersed himself in both academic and applied research environments. He initially served as a Researcher at the Human-like Perception Research Center, Zhejiang Laboratory from June to September 2021, contributing to cutting-edge studies in perception technologies.
In November 2021, Dr. Li joined the Department of Public Security at Fujian Police College as a Lecturer, and was later promoted to Associate Professor. His role encompasses teaching, guiding student research, and leading scientific inquiries into intelligent transportation and traffic safety systems. He is also an External Master’s Thesis Supervisor at the College of Big Data and Computer Science, Fuzhou University since December 2021, further reflecting his academic mentorship roles.
🔬 Contributions and Research Focus
Dr. Li has an impressive record of participation in high-level scientific research. His primary focus lies in electromagnetic tomography, traffic accident imaging, and intelligent transportation systems. He has been a Principal Investigator for multiple projects, including:
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“Large-scale Electromagnetic Tomography for Road Traffic Monitoring” (NSFC Project No. 62301159)
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“Dual-plane Linear Array Electromagnetic Tomography for Traffic Accident Imaging”
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“Urban Road Traffic Situation Assessment System” funded by Fujian’s Department of Finance
He is also a core participant in a significant ongoing NSFC project titled “Optimization of Delay Operation in Integrated Subway-Bus Networks in Metropolises”.
His work spans both theoretical modeling and applied systems, focusing on real-time data acquisition, traffic state estimation, and sensor technology for safety enhancement.
🏅 Accolades and Recognition
While explicit awards or honors are not detailed in the provided profile, Dr. Li’s consistent leadership in nationally funded research projects—particularly as a Principal Investigator on NSFC and provincial-level grants—is a strong indicator of peer recognition and institutional trust. His appointment as an Associate Professor within just a few years of completing his Ph.D. further underscores his rising prominence in the field.
🌍 Impact and Influence
Dr. Li’s work has direct societal implications, especially in improving urban traffic safety, accident response efficiency, and transportation infrastructure monitoring. His research contributes to China’s broader smart city initiatives and public security advancements, particularly in densely populated urban areas.
By bridging electrical engineering, traffic systems, and intelligent sensing, Dr. Li plays a pivotal role in making city transportation safer, more responsive, and more technologically advanced.
🚀 Legacy and Future Contributions
Looking forward, Dr. Li is poised to continue expanding the intersection of AI, electromagnetic sensing, and traffic control systems. His current NSFC and provincial projects are likely to yield further innovations in how we understand and manage traffic flow, detect anomalies, and respond to emergencies in real time.
With his expanding role as an educator and mentor, his influence will also be felt through the next generation of public safety and traffic engineering professionals in China. Dr. Li’s combination of academic rigor, inventive spirit, and societal relevance makes him a key figure in the evolution of smart transportation technologies.
đź“šPublications Top Notes
A Kalman Filtering Method on Time–Frequency Discrimination Analysis