Xiangtan University | China
Mr. Guizheng Guan is a highly accomplished researcher and engineer specializing in optical computing and photonic reservoir computing for brain-like models. He has been recognized with multiple awards, including the National Scholarship for Graduate Students, First-Class Scholarship at Shandong University of Technology, and Outstanding Graduate Student honors at Xiangtan University. His personal research focuses on leveraging delayed feedback semiconductor lasers, VCSELs, and laser arrays to develop high-speed, low-power, and compact photonic computing systems capable of chaotic time series prediction, multivariable task processing, and real-time mixed gas detection. He has published extensively in high-impact journals such as Neurocomputing, Neural Networks, and SPIE, demonstrating innovations in hybrid serial-parallel architectures, adaptive load balancing, and deep coupling of photonic systems. Additionally, he contributed to his supervisor’s research on high-precision micro-nano step height measurement using FMCW self-mixing interferometry. Mr. Guan has a strong foundation in mathematics and programming, proven through top awards in the National College Mathematics Competition and multiple ACM and Blue Bridge Cup contests. He also possesses practical experience in embedded systems, wireless network testing, and algorithm development for RF chip calibration. Throughout his academic and professional journey, he has demonstrated exceptional technical innovation, teamwork, and leadership skills, consistently achieving recognition at provincial, national, and international levels.
Profile: Orcid
Featured Publications
Liu, B., Guan, G., Ruan, Y., Yu, Y., Xi, J., Ji, H., & Tang, P. (2025). Micro–nano step height measurement using FMCW self-mixing interferometry. IEEE Transactions on Instrumentation and Measurement.
Guan, G., & Liu, B. (2025). Hybrid serial-parallel photonic reservoir computing based on single semiconductor laser with delayed optical feedback for multivariable task processing. Neurocomputing.