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About

Zheng Gong is a researcher at the intersection of bioinspired robotics, hydrodynamic sensing, and autonomous systems, with a particular focus on developing artificial lateral line (ALL) systems for underwater perception and navigation. Drawing inspiration from the sensory biology of fish, Gong has made significant contributions to the field of underwater source localization by pioneering sensor fusion approaches that combine pressure and flow velocity modalities — a departure from earlier single-modality systems. His 2021 paper on this topic has accumulated 63 citations, establishing him as a notable voice in underwater robotics sensing. Building on this foundation, his subsequent work on optimized sensor placement strategies for ALL systems demonstrates a rigorous, mathematically informed approach to maximizing hydrodynamic stimulation and detection efficiency. A standout contribution lies in his interdisciplinary 2024 study revealing that the distinctive head horns of eyeless cavefish serve a functional hydrodynamic sensing role, bridging evolutionary biology and engineering insight. More recently, Gong has expanded into terrestrial autonomous navigation, applying learning-based methods to off-road traversability estimation. Across these diverse domains, his research reflects a consistent drive to translate biological principles into practical robotic perception systems.