Chenyou Fan
Papers
1
Total Citations
6
H-Index
1
About
Chenyou Fan is a researcher advancing the frontiers of multi-agent perception and few-shot learning, with a focus on enabling collaborative intelligence among resource-constrained agents like drones and robots. Their seminal work, "Few-Shot Multi-Agent Perception" (2021, 6 citations), addresses a critical challenge: how multiple agents with limited local labeled data can cooperate to accurately predict query labels despite minimal communication and computation capabilities. This contribution bridges few-shot learning and multi-agent systems, offering scalable solutions for real-world deployments where data scarcity and collaboration constraints coexist. Fan’s research has implications for autonomous swarms, distributed sensing, and edge AI, where efficient, low-overhead learning is paramount. By tackling the intersection of data efficiency and decentralized coordination, Fan is shaping the next generation of intelligent, collaborative systems that can operate in data-sparse, communication-limited environments—a vital step toward practical multi-agent autonomy.
Research Focus
Key Achievements
Top Papers
- 1Few-Shot Multi-Agent Perception6 citations · 2021