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About
Zefan Ge is a researcher at the forefront of bio-inspired artificial intelligence and swarm robotics, with a particular focus on modeling collective motion in complex systems. His most notable contribution, the paper "Collective motion model inspired by fish school based on deep attention mechanism" (2025), introduces a novel deep attention network that captures the nuanced social interactions observed in biological groups like fish schools. This work bridges the gap between natural collective intelligence and artificial control systems, offering a scalable framework for coordinating swarm robotics. By leveraging attention mechanisms, Ge’s model improves how individual agents perceive and respond to their neighbors, addressing a long-standing challenge in decentralized multi-agent systems. Though early in its citation impact, the paper represents a significant step toward more adaptive and realistic swarm behaviors. Ge’s research holds promise for applications in autonomous drone fleets, environmental monitoring, and distributed sensing. His work reflects a growing trend of integrating deep learning with ethology, positioning him as an emerging voice in the intersection of artificial intelligence, robotics, and complex systems science.
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