Prof. Quanmin Zhu | Data Driven Decision Making | Best Researcher Award
Distinguished Professor at University of the West of England | United Kingdom
Professor Quanmin Zhu is a distinguished academic and leading authority in control systems engineering, currently serving at the School of Engineering, University of the West of England, Bristol. With a career grounded in rigorous research and scholarly excellence, he has significantly advanced the fields of complex system modelling, identification, and control through both theoretical innovation and practical application. His prolific contributions include the authorship of over 300 peer-reviewed publications and the editorial oversight of major works with prestigious publishers such as Springer and Elsevier. A Chartered Engineer and Fellow of the Institution of Engineering and Technology (FIET) as well as the Higher Education Academy (FHEA), Professor Zhu is widely recognized for his commitment to bridging the gap between academic research and industrial practice. His expertise has been instrumental in shaping methodologies that enhance system performance, reliability, and adaptability across diverse engineering domains. As Editor of Elsevier’s Emerging Methodologies and Applications in Modelling, Identification and Control series, he continues to influence emerging directions in modern control theory and intelligent systems. Professor Zhu’s academic leadership, combined with his dedication to mentorship and collaboration, underscores his enduring impact on the global engineering community and his role in fostering innovation at the intersection of computation, automation, and control science.
Featured Publications
Azar, A. T., & Zhu, Q. (2015). Advances and applications in sliding mode control systems.
Zhu, Q., & Azar, A. T. (2015). Complex system modelling and control through intelligent soft computations.
Li, S., Zhang, Y., & Zhu, Q. (2005). Nash-optimization enhanced distributed model predictive control applied to the Shell benchmark problem.
Billings, S. A., & Zhu, Q. M. (1994). Nonlinear model validation using correlation tests.
Chen, J., Zhu, Q., & Liu, Y. (2020). Modified Kalman filtering based multi-step-length gradient iterative algorithm for ARX models with random missing outputs.