Daniel Quinn
Papers
9
Total Citations
430
H-Index
6
About
Daniel Quinn is a leading researcher in bio-inspired robotics and fluid dynamics, whose work bridges the gap between animal locomotion and engineered systems. His primary research areas include fish-inspired swimming robots, tunable stiffness mechanisms, and animal flight and maneuverability. Quinn’s most impactful contribution is his investigation of how fish use tunable flexibility to maintain high swimming efficiency across varying speeds, a concept he has successfully applied to robotic fish. His 2021 paper on this topic has garnered 202 citations, highlighting its significance in the field. He has also explored how lovebirds navigate lateral gusts with minimal visual information, offering insights into bio-inspired flight control. Quinn’s work on spontaneous snapping-induced jet flows for soft swimming robots, inspired by manta rays, represents a novel approach to achieving fast and maneuverable underwater locomotion. Additionally, his studies on flow-mediated equilibrium altitudes for swimming foils near boundaries have advanced understanding of ground effects in aquatic locomotion. With over 400 total citations across his publications, Quinn’s research is shaping the future of agile, efficient robotic systems for both aerial and aquatic environments.
Research Focus
Key Achievements
Top Papers
- 1Tunable stiffness enables fast and efficient swimming in fish-like robots202 citations · 2021
- 2Tunable stiffness in fish robotics: mechanisms and advantages84 citations · 2021
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- 4Swimming freely near the ground leads to flow-mediated equilibrium altitudes42 citations · 2019
- 5How lovebirds maneuver through lateral gusts with minimal visual information27 citations · 2019
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- 8Streamwise and lateral maneuvers of a fish-inspired hydrofoil2 citations · 2021
- 9Wavenumber affects the lift of ray-inspired fins near a substrate1 citations · 2025