Rate My Professor Guodong Shi

Guodong Shi is an Associate Professor in Mechatronic Engineering in the Faculty of Engineering at the University of Sydney. He is affiliated with the Australian Centre for Field Robotics (ACFR) since 2019 and serves as a Chief Investigator for ARIAM, the ARC Research Hub in Intelligent Robotic Autonomous Systems. Shi received his B.Sc. degree in mathematics and applied mathematics from the School of Mathematics, Shandong University, Jinan, China, in 2005, and his Ph.D. degree in systems theory from the Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China, in 2010. His career includes a Postdoctoral Researcher position at the ACCESS Linnaeus Centre, KTH Royal Institute of Technology, Stockholm, Sweden, from 2010 to 2014, followed by roles as Lecturer, Senior Lecturer, and Future Engineering Research Leadership Fellow at the Research School of Engineering, Australian National University, from 2014 to 2018.

Guodong Shi's research investigates the structural and functional aspects of networks motivated by engineering, social, and quantum systems, utilizing tools from control theory, optimization, computational complexity, and stochastic decision-making. His primary interests encompass distributed control systems, quantum networking and decisions, and social opinion dynamics. Shi's contributions have enhanced comprehension of adversaries and biases in social opinion dynamics, pioneered fundamental distributed control and optimization algorithms, devised novel privacy-protection mechanisms, and propelled scalability in quantum information processing. His scholarly impact is evidenced by over 5,000 citations and an h-index of 35 on Google Scholar. He has obtained funding via ARC Discovery Projects, including a recent award with Professor Ian Manchester. Shi engages in public seminars, such as 'When Robots Meet Qubits,' and holds roles like arXiv moderator for the IEEE Control Systems Society. He supervises PhD projects on algorithmic defenses against misinformation in social networks.