Lu Renquan

Professor Lu Renquan is a distinguished faculty member at Guangdong University of Technology's School of Automation, serving as Director of the Institute of Science, Technology and Humanities and holding the rank of Professor and PhD Supervisor. With over 20 years of academic leadership, he directs major research initiatives in networked control systems and autonomous technologies.

His educational foundation includes:

• Master in Materials Engineering, Lanzhou University of Technology (1998-2001)
• Ph.D. in Control Science and Engineering, Zhejiang University (2001-2004)
• Postdoctoral Research, Zhejiang University (2005-2007)
• Visiting Scholar, Universiti Kuala Lumpur (2007)

Professor Lu's research pioneers Networked Control Systems, Intelligent Decision and Collaborative Control, and Unmanned Autonomous Systems. His work integrates robust control theory with industrial applications, driving innovations in autonomous vehicle coordination and data-driven manufacturing. With over 140 SCI publications including 60+ IEEE Transactions papers and 9 Automatica articles, his research demonstrates significant theoretical depth and practical impact across engineering disciplines.

His scientific recognition includes:

• Ministry of Education Natural Science Award First Prize (2019, lead recipient)
• Three additional Ministry of Education/National awards (2011-2016)
• National Outstanding Youth Fund recipient
• State Council Special Allowance recipient

Professor Lu actively mentors students while leading substantial research programs. His current portfolio includes a national key R&D project on manufacturing data spaces, Guangdong's Unmanned Autonomous System Collaborative Control Team, and direction of the Provincial Key Laboratory for Intelligent Decision and Collaborative Control. He teaches core courses in robust control and automatic systems while guiding student teams in national competitions like the 'Challenge Cup'.

He directs the Guangdong Provincial Key Laboratory of Intelligent Decision and Collaborative Control, which focuses on advancing collaborative algorithms for unmanned systems and industrial automation through interdisciplinary research in networked control theory and big data applications.