Ruiqi Liu

Wuhan National Laboratory for Optoelectronics

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About

Ruiqi Liu is a rising innovator in the field of soft robotics, with a focused expertise in magnetic actuation and intelligent control systems. Their research centers on advancing the capabilities of magnetic soft robots (MSRs) and liquid-based robotic systems, particularly through the integration of machine learning to overcome traditional heuristic design limitations. Liu’s most impactful contribution, "Adaptive Actuation of Magnetic Soft Robots Using Deep Reinforcement Learning" (2023), has garnered 37 citations, marking a significant step toward autonomous, adaptive control in untethered soft robotics. This work demonstrates how deep reinforcement learning can replace manual tuning, enabling robots to navigate complex environments with unprecedented precision. In their more recent exploration of multifunctional liquid robotics with ferrofluids (2024), Liu expands the frontier by addressing fabrication, control, and sensing in a single platform, hinting at future applications in biomedical devices and micro-manipulation. Though early in their career, Liu’s work is already shaping how researchers approach the intersection of soft materials and artificial intelligence, promising smarter, more versatile robotic systems.