Papers
2
Total Citations
113
H-Index
2
About
Quan Feng is a rising innovator at the intersection of smart materials and agricultural technology. His research primarily focuses on developing advanced soft actuators and deploying efficient deep learning models for precision agriculture. Feng’s most impactful contribution is the scalable fabrication of functionalized liquid crystal elastomer (LCE) fiber soft actuators. His 2023 paper on this topic, which has garnered 109 citations, demonstrates how these fibers achieve large, reversible deformations with multi-stimulus responses, including a novel photoelectric conversion capability. This work overcomes a critical bottleneck in soft robotics by enabling tailorable photo-electro-thermal responsiveness in a scalable fiber format. In a parallel effort to bridge AI with real-world farming, Feng addresses the challenge of deploying plant protection robots on resource-limited edge devices. His 2024 work introduces a spot-adaptive knowledge distillation method that compresses large disease recognition networks without sacrificing accuracy, making AI-driven crop monitoring practical for field use. By pioneering both high-performance soft actuators and efficient agricultural AI, Quan Feng is shaping the future of responsive materials and intelligent, sustainable farming systems.
Research Focus
Key Achievements
Top Papers
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