Prof. Fazhi Song | Control Systems | Research Excellence Award

Professor | Harbin Institute of Technology | China

Dr. Fazhi Song, a Professor at the Harbin Institute of Technology specializing in control science, motion control, and precision engineering, is an accomplished researcher whose work advances high-end manufacturing and ultra-precision motion systems. He holds advanced degrees culminating in a Ph.D. in Control Science and Engineering, with academic training focused on system identification, learning control, and precision motion technologies. Throughout his professional career, he has led major research initiatives in motion generation, performance control, and accuracy retentivity for advanced manufacturing equipment, contributing to national and provincial projects and collaborating with leading industrial partners on precision motion systems. His research centers on high-precision mechanical servo systems, uncertainty-robust learning control, multi-DOF motion coordination, and advanced control strategies for lithography-level equipment, supported by a strong record of publications, patents, and technical innovations. He has authored numerous peer-reviewed articles, contributed to an academic monograph, and advanced methodologies widely cited in the fields of precision engineering and automation, reflected through 45 citations, 9 documents, and an h-index of the candidate. His achievements include significant awards from national academic societies recognizing technological innovation, along with contributions as a guest editor for respected journals, session chair for international conferences, and active membership in IEEE and major professional automation and instrumentation societies. Dr. Song’s leadership in research, editorial service, and professional engagement underscores his commitment to advancing ultra-precision control technologies and cultivating scientific excellence in the global engineering community.

Profiles: Scopus | ORCID

Featured Publications

Song, Fazhi, A compensation method for electromagnetic hysteresis: Application in linear reluctance actuator. J. Magn. Magn. Mater., 2025.*

Song, Fazhi, Crest factor minimization of multisine signals based on the Chebyshev norm approximation method: With application to wafer stage FRF identification. Results Eng., 2025.*

Song, Fazhi, Identification for Precision Mechatronics: An Auxiliary Model-Based Hierarchical Refined Instrumental Variable Algorithm. Int. J. Robust Nonlinear Control., 2025.*

Song, Fazhi, Beyond Performance of Learning Control Subject to Uncertainties and Noise: A Frequency-Domain Approach Applied to Wafer Stages. IEEE/CAA J. Autom. Sinica., 2025, 5 citations.*

Ms. Siqin Liao | Control Systems & Optimization | Best Researcher Award

Student | The School of Computer Science, Guangdong University of Technology | China

Siqin Liao is a Ph.D. candidate at the School of Computer Science, Guangdong University of Technology, specializing in control theory and intelligent systems. He holds a Master of Engineering in Control Engineering from Guangdong University of Technology and a Bachelor of Engineering in Electrical Engineering and Automation from Xinyu University, and has completed a visiting research program at the University of Adelaide, Australia. His research focuses on asynchronous control of Markov jump systems, cooperative control of multi-agent systems, and network security control. Liao has published seven SCI-indexed papers in leading journals such as IEEE Transactions on Cybernetics and Systems & Control Letters, contributing novel control methodologies for stochastic and networked systems under uncertainty and cyberattacks. He has participated in provincial-level projects funded by the Guangdong Basic and Applied Basic Research Foundation and collaborates internationally on control design research. His scholarly impact includes over 100 citations, with recognition for his first-author and corresponding-author publications. As a student member of IEEE, he upholds academic excellence and innovation in control system theory. His achievements have earned him awards such as the First Prize in the Siemens Cup China Intelligent Manufacturing Challenge and the Third Prize in the China Robowork Competition, highlighting both his technical expertise and leadership in engineering research. His research record includes 80 citations across 7 publications with an h-index of 2, reflecting his growing academic influence.

Profile: Scopus

Featured Publications

Siqin Liao*, Zheng-Guang Wu, Yuanqing Wu. Constrained quadratic control for Markov jump systems with multiplicative noise. Syst. Control Lett., 2025, 203:06–27.

Siqin Liao*, Yuanqing Wu, Zheng-Guang Wu, Peng Shi. Design on dynamic event and self-triggered control for systems with Markov jumps and denial-of-service attacks. J. Franklin Inst., 2025, doi:10.1016/j.jfranklin.2025.108006.

Siqin Liao, Zheng-Guang Wu, Yuanqing Wu*. Control for Markov jump systems with partially unknown transition probabilities under denial-of-service attacks. Int. J. Robust Nonlinear Control., 2025, doi:10.1002/rnc.70142.