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About

Zheng-Shou Chen is a rising researcher in bio-inspired underwater robotics, specializing in the hydrodynamic analysis and kinematic modeling of biomimetic pectoral fins. His work focuses on understanding how cownose rays achieve efficient propulsion through flexible fin motions, leading to the development of advanced computational frameworks for predicting fin performance. Chen’s most-cited paper, “Kinematic modelling and hydrodynamic analysis of biomimetic pectoral fins of cownose ray” (2024, 12 citations), establishes foundational insights into ray-inspired locomotion. He further advanced this field with an AVOA-optimized CNN-BILSTM-SENet framework (2025, 3 citations) that enhances prediction accuracy for bionic fin hydrodynamics. Chen also addresses critical challenges in autonomous underwater vehicles, proposing optimization strategies for bio-inspired lateral line sensor arrays to improve sensing in extreme environments where conventional methods fail. His interdisciplinary approach—integrating computational fluid dynamics, machine learning, and biomimetics—positions him at the forefront of next-generation underwater robotics. With growing citation impact and innovative contributions to autonomous sensing and propulsion, Chen’s work is paving the way for more agile, efficient, and perceptive underwater vehicles.