Shengkun Liao Of Tianjin University of Technology and Education, China
Shengkun Liao is an accomplished graduate student at Tianjin University of Technology and Education, specializing in the development and optimization of intelligent vehicle technologies and new energy vehicle systems. His expertise spans energy recovery systems, vehicle control units, intelligent navigation, and autonomous charging mechanisms. With research published in EI- and JCR-indexed journals, Liao combines technical innovation with practical automotive engineering applications. His work integrates advanced algorithms, Raspberry Pi systems, and ROS frameworks, earning him recognition through multiple awards in national and provincial competitions. He is committed to driving innovation in sustainable and intelligent transportation systems.
Professional Profile
ORCID
Education
Liao is currently pursuing graduate-level studies at Tianjin University of Technology and Education, where he has built a solid academic foundation in electrical, mechanical, and computational engineering aspects of vehicle systems. His curriculum emphasizes applied engineering design, intelligent control, and algorithm development, enabling him to approach research from both a theoretical and application-oriented perspective. This educational journey has been marked by active participation in advanced coursework, laboratory experimentation, and collaborative projects that align closely with his research in new energy vehicles and intelligent transportation systems.
Experience
In his academic career, Liao has focused on projects that merge cutting-edge computational methods with practical engineering applications. His work includes the optimization of energy recovery systems for battery electric vehicles using intelligent algorithms, and the enhancement of autonomous vehicle charging navigation systems through the integration of the Bidirectional A* Algorithm with the YOLOv11n model. He has also conducted experimental studies on charging and discharging modules for new energy vehicles. These experiences have provided hands-on exposure to system design, algorithm optimization, and interdisciplinary problem-solving, bridging gaps between academic research and industry needs.
Research Focus
Liao’s research is centered on advancing the performance, efficiency, and autonomy of new energy vehicles. His areas of expertise include the development and optimization of energy recovery systems to improve vehicle efficiency, automotive vehicle control unit (VCU) development, and the refinement of intelligent algorithms for navigation and recognition. He also explores the integration of autonomous charging systems with machine vision technologies, leveraging platforms such as Raspberry Pi and ROS for practical implementation. By combining artificial intelligence with robust hardware solutions, his research aims to enable smarter, more efficient, and environmentally sustainable transportation systems.
Awards & Honors
Liao has been recognized for his innovative research and technical achievements through multiple national and provincial awards in engineering and innovation competitions. These honors highlight his ability to design and implement effective engineering solutions that address real-world challenges in the automotive and transportation sectors. His competitive success demonstrates not only technical expertise but also creativity, leadership, and a capacity for translating research into impactful applications. These accolades underscore his standing as a rising figure in the field of intelligent vehicle technology.
Publication Top Notes
Title: Optimization of the Energy Recovery System for Battery Electric Vehicles Based on Intelligent Algorithms
Authors: S Liao
Journal: International Journal of Vehicle Design and Intelligent Systems
Title: Optimization of a Navigation System for Autonomous Charging of Intelligent Vehicles Based on the Bidirectional A* Algorithm and YOLOv11n Model
Authors: S Liao
Journal: Journal of Intelligent Transportation and Automation
Title: Experimental Study on the Charging and Discharging Module of New Energy Vehicles
Authors: S Liao
Journal: Journal of Advanced Automotive Engineering
Conclusion
Through a combination of strong academic preparation, innovative research, and recognized achievements, Liao has established himself as an emerging leader in intelligent transportation and new energy vehicle technology. His work embodies the integration of advanced computational methods, sustainable engineering practices, and practical implementation strategies. By addressing key challenges in vehicle energy efficiency, autonomous navigation, and system optimization, his contributions are paving the way for more efficient, intelligent, and environmentally responsible transportation solutions. His trajectory reflects both technical excellence and a deep commitment to the progress of automotive engineering research.