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Sichuan University has established itself as a powerhouse in intelligent materials, flexible electronics, and human-machine interaction technologies, with research that sits at the dynamic intersection of materials science, robotics, and artificial intelligence. The institution's publication record reflects a deep and sustained commitment to solving some of the most persistent challenges in soft robotics, wearable sensing, and adaptive systems—making it an increasingly significant voice in the global robotics and AI research community. At the heart of Sichuan University's contributions is an extraordinary body of work on self-healing, multi-responsive smart materials. Researchers here have pioneered hydrogel-based sensors capable of autonomous repair, flexible strain sensing, and seamless human-machine interaction, with landmark papers accumulating hundreds of citations and reshaping how the field approaches electronic skin design. Their development of conductive self-healing hydrogels, MXene-based soft actuators inspired by bamboo microstructure, and liquid-crystalline networks with photocontrolled actuation demonstrates a sophisticated ability to translate biological principles into functional robotic components. Work on 3D shape measurement methods, pulse-coupled neural networks for real-time robot path planning, and additive manufacturing of functional polymeric devices further illustrates the university's broad technical reach. The institution's researchers have also explored the societal dimensions of robotics, examining customer-robot interactions and the macroeconomic impact of industrial robots on carbon emissions—reflecting a genuinely interdisciplinary culture. With collectively thousands of citations across these domains, Sichuan University offers prospective students and collaborators access to cutting-edge laboratories working on the materials that will define next-generation soft robots, wearable health monitors, and intelligent actuators. Its blend of fundamental materials innovation and applied systems thinking makes it a compelling partner for any research agenda aimed at building the physical intelligence of tomorrow's machines.