Ziye Zhou

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About

Ziye Zhou is a rising researcher in swarm intelligence and bio-inspired robotics, whose work bridges the gap between biological collective behaviors and artificial multi-agent systems. Their primary research areas include pursuit–evasion dynamics, group movement modeling, and biomimetic robotic formation control. Zhou’s major contributions center on uncovering the fundamental mechanisms that govern animal group behaviors—such as fish schooling and milling—and translating these principles into computational models and robotic applications. Their highly cited survey on the pursuit–evasion problem in swarm intelligence (31 citations) provides a critical framework for understanding how complex functions emerge from simple biological rules. Zhou’s innovative “fellow-following principle” model (7 citations) offers a more realistic representation of fish school movements, while their circular formation method for biomimetic robotic fish (5 citations) demonstrates practical applications by distilling fish milling into forward-following and circular topological communication mechanisms. This work not only advances theoretical understanding of collective animal behavior but also provides tangible algorithms for coordinating autonomous robotic swarms, making Zhou’s research valuable for both biologists studying natural systems and engineers designing distributed artificial intelligence.