Jifu Tan

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About

Jifu Tan is a leading researcher in biomimetic hydrodynamics and computational fluid dynamics, with a primary focus on unraveling the complex mechanics of fish swimming to advance robotic fish design. His most notable contribution is the development of an integrated immersed boundary–lattice Boltzmann method combined with dynamic mode decomposition, which he applied in his highly cited 2022 paper (43 citations) to investigate flow patterns around bionic fish. This work provides a powerful computational framework for analyzing vortex structures and energy-efficient propulsion mechanisms. Tan’s more recent 2025 study introduces a novel spatio-temporal analysis of shear traction dynamics on fish body surfaces, offering unprecedented insight into the surface stress distributions that govern swimming efficiency. This research directly informs the shape optimization and structural design of robotic fish, as well as the coordinated control of schooling robotic fish. By bridging high-fidelity simulation with biological locomotion principles, Tan’s work is shaping the next generation of bio-inspired underwater vehicles, making him a key figure in the intersection of computational mechanics and biomimetic engineering.