Dr. yinglu Song South | China University of Technology | China
Dr. Song Yinglu, originally from Nanning, Guangxi, is a passionate and talented postgraduate researcher specializing in Control Engineering and AI applications. A graduate student at the University of Science and Technology Beijing, he consistently demonstrates excellence in academics, innovation, and hands-on engineering. With a deep-rooted interest in smart sensing, machine vision, and embedded systems, Song has actively led and participated in multiple cross-disciplinary research projects with real-world applications. His profile reflects a combination of technical proficiency, creativity, and leadership, highlighted by his patent portfolio and national awards. Beyond academics, he is actively involved in volunteerism and student affairs. Through self-driven initiatives and collaboration with research institutions and enterprises, he strives to make meaningful contributions to engineering and intelligent systems. Known for his resilience and enthusiasm, Song Yinglu is well-positioned to become a transformative force in technology and applied research, making him an exceptional candidate for the Best Young Researcher Award.
Profile
scopus
Education
Dr. Song Yinglu pursued his Master’s in Electronic Information (Control Engineering) at the University of Science and Technology Beijing (Project 211), where he ranked 8th out of 22 students and completed a rigorous curriculum including Machine Learning, Pattern Recognition, Data Mining, and Artificial Intelligence. Prior to this, he earned his Bachelor’s degree in Measurement & Control Technology and Instrumentation from Guangxi University of Science and Technology, ranking 10th out of 86 peers. His academic foundation is grounded in both software and hardware principles—ranging from analog and digital electronics to microcontrollers and system design. These qualifications have equipped him with a robust analytical mindset and technical expertise. His academic choices reflect a progressive journey toward automation and AI-driven systems. This strong educational background underpins his research efforts in control systems, signal processing, and intelligent sensing, and provides the foundation for his work in academia, industry, and national innovation platforms.
Experience
Dr. Song’s experience is rich in research, development, and real-world engineering deployment. He has led pioneering projects like “Contactless Driver Status Detection Using WiFi Channel State Information” using tools such as MATLAB, Python, Linux, and LSTM models to detect driver fatigue and health. At Sinoma Science & Technology, he collaborated on machine vision systems for wind turbine blade manufacturing, enhancing defect detection capabilities. His internship at SenseTime Technology involved intelligent vending systems using computer vision, while his engineering tenure at Shenzhen Futae Hong focused on PCB testing and hardware troubleshooting. In campus life, he played a leadership role in organizing national-level competitions and technical workshops, managing student records, and supporting graduate entrance evaluations. Across roles, Song has demonstrated hands-on capabilities, team collaboration, and a practical mindset, complementing his academic rigor. His field adaptability, combined with extensive development skills and systematic thinking, defines him as a well-rounded and accomplished young technologist.
Research Interests
Dr. Song Yinglu’s research interests span across wireless sensing, machine vision, and embedded systems, with a specific focus on smart detection using WiFi CSI, driver safety monitoring, and industrial quality control. He is particularly interested in applying deep learning techniques like LSTM and AI to enhance non-contact human monitoring systems, offering safer and more efficient solutions in transportation and healthcare. His machine vision work addresses automation in manufacturing processes—like detecting glue application issues in wind turbine blades. He also has experience with environmental sensing, as seen in his early innovation projects involving unmanned boats and CAN bus-based safety systems. Combining signal processing with AI and embedded technologies, he seeks to bridge real-world sensing challenges with intelligent computing frameworks. His research goal is to develop intuitive, low-cost intelligent systems for real-time human-machine interaction and environmental monitoring, driving future advancements in IoT, automation, and smart cities.
Awards & Recognition
Dr. Song has consistently earned accolades throughout his academic and professional journey. Notably, he received National Third Prize (×2) in the COMAP Mathematical Contest in Modeling and Provincial Third Prizes (×2) in the National Undergraduate Electronic Design Competition. His innovative project on unmanned water quality detection won the Guangxi Bronze Medal at the China International “Internet+” Innovation & Entrepreneurship Competition. He also earned multiple Academic Scholarships, Science and Technology Excellence Awards, and was recognized as an Outstanding Class Leader (×3). As a team leader and core member, he has played pivotal roles in numerous award-winning projects in both university and enterprise settings. His involvement in various competitions displays not only technical skill but also effective team leadership, project management, and innovative thinking. These awards are testaments to his high potential, ingenuity, and consistency—making him a standout candidate for competitive national and international research honors.
Publications Top Notes
Design of an Intelligent Fish Tank Control System Based on IoT
A Method for Enhanced WiFi CSI-Based Human Breathing Signal Detection
In-Car Environment Monitoring and Safety Control System Based on CAN
A Robot Vision Positioning Device
Defect Detection System for Natural Gas Pipelines
Conclusion
Dr. Song Yinglu is a forward-thinking, high-achieving researcher whose academic background, technical prowess, and innovative mindset make him an ideal nominee for the Best Young Researcher Award. His excellence spans theoretical learning, hands-on engineering, team leadership, and real-world problem-solving. With contributions ranging from AI-powered detection systems to embedded hardware development, he bridges the gap between academia and industry. His work has been recognized by multiple institutions and published in scholarly formats, with granted patents reflecting practical innovation. Moreover, his commitment to student leadership, volunteering, and science communication further highlights his all-around capability. Song Yinglu represents the next generation of global researchers, and his multi-disciplinary approach promises impactful contributions to science, technology, and society. Awarding him would not only recognize his achievements but also encourage a future of excellence in AI and engineering innovation.