Zhengyan Qin
Papers
1
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1
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About
Zhengyan Qin is a rising researcher in the field of distributed control and optimization for multiagent systems, with a focus on heterogeneous linear dynamics and disturbance rejection. Their work bridges the gap between theoretical optimization and practical system robustness, particularly through the innovative use of timescale separation and momentum-based techniques. In their most-cited paper, "Momentum-Based Distributed Disturbance Feedback Optimization of Heterogeneous Multiagent Systems: A Timescale Separation Approach" (2025), Qin addresses the challenging problem of driving agents subject to disturbances toward the optimal solution of a global nonconvex objective function. This contribution introduces a novel distributed disturbance feedback framework that leverages momentum to accelerate convergence and enhance resilience, marking a significant step forward in the control of complex, real-world networks. While still early in their career, Qin’s work demonstrates a strong potential to influence autonomous systems, smart grids, and robotic coordination. Their research is particularly valuable for students and engineers seeking robust, scalable solutions for multiagent systems operating under uncertainty.
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