Xinyi Fan

Zhejiang University, Shanghai Jiao Tong University

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About

Xinyi Fan is a researcher at the forefront of neuromorphic engineering and intelligent robotics, whose work bridges the gap between advanced materials and autonomous systems. Her most impactful contribution is the development of a "plasmon-enhanced 2D material neural network" for artificial visual perception and recognition (2024, 48 citations). This pioneering work demonstrates a high-performance neuromorphic visual system that integrates photosensor arrays with neural network processing, offering a path toward more efficient and compact machine vision for applications in autonomous vehicles and robotics—a significant departure from traditional silicon-based technologies. Earlier in her career, Fan tackled complex problems in multi-agent systems, specifically addressing the challenge of indoor pursuit-evasion games (PEGs) with a novel pursuit strategy for capturing fast evaders (2012). This work, implemented on multiple mobile robots with wireless communication, showcases her foundational expertise in robotics and control theory. With a combined citation impact that underscores her growing influence, Fan's research is shaping the future of intelligent systems, from biomimetic vision to autonomous decision-making. Her work is essential reading for anyone interested in the convergence of materials science, neural networks, and robotics.