Dan Ye
Papers
8
Total Citations
87
H-Index
4
About
Dan Ye’s research lies at the intersection of multi-agent system security, human-robot interaction, and bio-signal-driven rehabilitation robotics. His most influential work, “Ripple effect of cooperative attacks in multi-agent systems: Results on minimum attack targets” (44 citations), addresses a critical vulnerability in distributed networks by identifying the minimum number of agents that must be compromised to destabilize the entire system—a foundational contribution to resilient control. In the domain of human-robot interaction, Ye pioneered the use of surface electromyography (sEMG) signals for intuitive control, as demonstrated in his highly cited 2020 paper on a temporally smoothed MLP regression scheme for continuous knee/ankle angle estimation (21 citations). This work, alongside his studies on motion intention estimation and ankle rehabilitation robot control, has advanced assistive technologies for stroke patients and the elderly. Ye also contributed to fault-tolerant control for nonlinear systems and novel data-driven methods for shape memory alloy actuators. With a growing citation footprint and a clear trajectory from theoretical security to practical rehabilitation, Ye’s work bridges foundational control theory and real-world biomedical applications.
Research Focus
Key Achievements
Top Papers
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- 4Ankle rehabilitation robot control based on biological signals4 citations · 2017
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- 6sEMG Based Movement Quantitative Estimation of Joins Using SVM Method3 citations · 2014
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