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About

Mingyang Sun is a robotics and cybersecurity researcher whose work spans industrial robot security, multi-robot coordination, and embodied AI systems. His most influential contribution, "Security of Industrial Robots: Vulnerabilities, Attacks, and Mitigations" (2022, 49 citations), established a foundational framework for understanding cyber-physical threats in smart manufacturing environments, addressing how networked industrial robots can be exploited and defended — a timely and increasingly critical concern as automation expands globally. Building on his robotics expertise, Sun has also advanced multi-robot systems research, developing an improved auction algorithm for dynamic task allocation (2021, 9 citations) and applying deep reinforcement learning to multi-robot coverage path planning (2021, 4 citations), both of which tackle real-world coordination challenges in autonomous systems. His more recent work pushes into the frontier of embodied AI, with "Quart-Online" (2025) addressing latency challenges in deploying multimodal large language models on quadruped robots — a technically demanding problem at the intersection of vision, language, and physical action. Across these domains, Sun demonstrates a consistent drive to make robotic systems both smarter and more secure.