University of Science and Technology of China | China
Author Profile
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Early Academic Pursuits
Chen Zonghai's academic journey commenced with a Bachelor's degree in Systems Science and Management Science from USTC, spanning from 1983 to 1988. He continued his education at USTC, achieving a Master's in Control Science and Engineering from 1988 to 1991.
Professional Endeavors
Chen Zonghai's career began as a Teaching Assistant at USTC's Department of Automation from 1991 to 1993. Progressing through the academic ranks, he served as a Lecturer from 1993 to 1995, an Associate Professor from 1995 to 1998, and has held the position of Professor since 1998. His work primarily focused on modeling, simulation, optimization of petrochemical processes, and later expanded into control of complex systems, intelligent science, robotics technology, and green energy.
Contributions and Research Focus
With a profound impact in the field, Chen Zonghai's research spans diverse areas, including modeling and control of complex systems, intelligent science, robotics technology, and green energy. His research interests also encompass fuzzy logic applications, renewable energy vehicles, and decision-making processes.
Accolades and Recognition
Chen Zonghai's exemplary contributions have earned him 13 national or local state technology awards in China. He holds credit for applying for 40 national patents and has an extensive publication record with over 450 papers and 3 monographs.
Impact and Influence
Chen Zonghai's influence extends beyond academia, with significant contributions to the technological landscape. His work on power lithium battery management systems, intelligent control technology for wind-solar hybrid energy, and simulation training systems have garnered national recognition.
Legacy and Future Contributions
As a Professor and Doctoral tutor at USTC, Chen Zonghai continues to shape the future of control science and engineering. His legacy includes numerous awards, a prolific publication record, and advancements in technology. His ongoing research projects, such as intelligent information representation and adaptation techniques for renewable energy vehicles, reflect his commitment to addressing contemporary challenges in the field.
Notable Publications
End-to-end deep learning powered battery state of health estimation considering multi-neighboring incomplete charging data 2024
A LiDAR SLAM System With Geometry Feature Group-Based Stable Feature Selection and Three-Stage Loop Closure Optimization 2023 (1)
Lifelong Vehicle Trajectory Prediction Framework Based on Generative Replay 2023