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About

Chengjun Wang is a pioneering researcher in soft robotics, bioinspired engineering, and intelligent automation. His work centers on developing adaptive, safe, and resilient robotic systems that mimic biological organisms, with a particular focus on fully soft robots and deep-sea exploration. Wang’s most influential contribution is the creation of soft ultrathin electronics innervated adaptive fully soft robots (2018, 428 citations), which advanced the field by enabling fully soft-bodied machines capable of complex motions without rigid components. His 2023 study on bioinspired soft robots for deep-sea exploration (199 citations) introduced a paradigm shift, demonstrating that soft robots can withstand extreme ocean pressures without heavy pressure vessels, opening new frontiers for marine science. Wang also explores thermally responsive liquid crystal elastomers for bimorph soft robots (2019, 28 citations) and develops nature-inspired algorithms, such as the Genghis Khan shark optimized algorithm for robotic trajectory planning (2024, 12 citations). His recent work includes real-time detection and instance segmentation for agricultural robots (2024, 4 citations) and rigid–flexible coupling grippers for industrial sorting (2024, 3 citations). With over 670 total citations, Wang’s research bridges fundamental materials science and practical robotics, offering transformative solutions for exploration, manufacturing, and agriculture.