Yufan Zhai

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About

Yufan Zhai is a leading researcher in bio-inspired robotics and fluid sensing, with a focus on replicating the extraordinary sensory capabilities of aquatic organisms. His primary research areas include artificial lateral line systems, fish-like robot locomotion, and flow-aided control mechanisms. Zhai’s major contribution lies in advancing the understanding and application of lateral line-inspired flow sensors, which enable underwater robots to perceive and interpret complex fluid environments—a critical step toward autonomous aquatic navigation. His influential 2021 review on fish lateral line inspired flow sensors and flow-aided control, with 68 citations, has become a foundational reference in the field, synthesizing years of progress and charting future directions. In his more recent 2025 work, Zhai introduced an interpretable approach using mode decomposition analysis to estimate self-motion in fish-like robots, achieving 14 citations in a short period. This work directly addresses the long-standing challenge of accurately distinguishing self-generated motion from environmental flow disturbances. Zhai’s research not only deepens our understanding of biological sensing but also paves the way for more agile, autonomous underwater vehicles.