Assoc Prof Dr.Yong Liang , College of Mechanical and Control Engineering, Guilin University of TechnologyChina
Assoc Prof Dr. Yong Liang is a distinguished academic at the College of Mechanical and Control Engineering, Guilin University of Technology, China. With a robust background in mechanical engineering, Dr. Liang’s research interests encompass advanced manufacturing technologies, robotics, and control systems.
Summary:
Assoc. Prof. Dr. Yong Liang is a dedicated researcher and educator with a robust academic background and a focused research agenda in emerging fields such as small sample learning, edge intelligence, and intelligent robots. His recent accolades, including the Chapek Award, reflect his significant contributions to integrating robotics education with industry needs. Dr. Liang’s work is both innovative and impactful, making him a strong candidate for the Best Researcher Award.
Education :
Mr. Yong Liang is a dedicated individual on a journey of continuous learning and academic achievement. He pursued his undergraduate degree at Wuhan Science and Technology Institute in 2005, laying a solid foundation in technology and engineering. Furthering his education, he earned a Master’s degree from Guilin University of Electronic and Technology in 2008, where he deepened his knowledge in electronic engineering. His thirst for knowledge did not stop there; in 2016, he received a Ph.D. degree from the College of Mechanical and Electronic Engineering, Northwest A&F University. His educational path reflects a commitment to the ever-evolving field of technology, showcasing a passion for electronic engineering and a determination to delve deeper into the world of intelligent robots.
Professional Skills:
Yong Liang not only excels academically but also possesses outstanding skills that have earned him recognition in the professional world. In 2024, he was awarded the prestigious Chapek Award, which honors excellence in integrating robotics education and the robotics industry, particularly as an Industry Education Integration Teacher. Over the past three years, he has published six research papers focusing on small sample learning, edge computing, FPGA, and related fields. His skills, awards, and achievements reflect a deep passion for learning and a commitment to excellence, setting him apart as a leader in his field.
Experience:
Mr. Yong Liang’s professional journey is marked by a continuous pursuit of growth and innovation. After earning his Master’s degree in 2008, he joined a college where he taught electronic courses such as Analog Electronics Technology, Digital Electronic Technology, Microcontroller Systems, and FPGA Principles and Applications. However, realizing that his technological perspective needed to be broader, he left academia to pursue a doctoral degree. Upon completing his Ph.D. in 2016, he joined Guilin University of Technology as both a teacher and a researcher. There, he formed an intelligent robot research team, which has made significant achievements in the field over the years. His experience highlights a blend of teaching and research, underpinned by a continuous drive to innovate and expand his expertise.
Research Focus:
Mr. Yong Liang is a tech enthusiast with a keen interest in cutting-edge advancements in small sample learning, intelligent robots, edge intelligence, and Green AI. His research explores the intersections of artificial intelligence and edge computing with a focus on low-power requirements. He is particularly interested in decentralized edge intelligence and collaborative deep learning, areas that promise to revolutionize how we think about and implement intelligent systems. His dedication to these fields reflects a commitment to shaping the future of technology, where seamless connectivity and intelligent systems pave the way for transformative innovations.
Conclusion:
Dr. Yong Liang is highly suitable for the Best Researcher Award. His strengths in cutting-edge research, educational contributions, and recent recognition align well with the award criteria. To further enhance his candidacy, he could focus on broadening his technological perspective through interdisciplinary research and increasing his publication volume and international collaborations. Overall, his achievements and commitment to advancing technology through research make him a deserving candidate for this prestigious award.
Publications :
- Research on Convolutional Neural Network Inference Acceleration and Performance Optimization for Edge Intelligence
Journal: Sensors
Published Year: 2024
- Research and Implementation of Adaptive Stereo Matching Algorithm Based on ZYNQ
Journal: Journal of Real-Time Image Processing
Published Year: 2024