Papers
2
Total Citations
13
H-Index
2
About
Yiran Hu is a rising researcher at the intersection of soft robotics and intelligent autonomous systems, with key contributions in magnetic soft continuum robots and safe task planning using large language models (LLMs). Hu’s work on flexible magnetic soft continuum robots, published in 2023 and garnering 7 citations, addresses the critical challenge of developing steerable, remotely controlled robots capable of analyzing mechanical properties of biological tissue during intravital procedures—a breakthrough for microscale manipulation and measurement in biomedical applications. In 2025, Hu advanced the field of robot autonomy with the paper “SELP: Generating Safe and Efficient Task Plans for Robot Agents with Large Language Models,” which has already earned 6 citations. This work tackles the persistent problem of ensuring robot agents adhere to user-specified constraints when executing complex, long-horizon natural language commands, thereby enhancing both safety and efficiency in real-world deployments. By bridging soft robotics and AI-driven planning, Hu demonstrates a unique ability to integrate physical dexterity with cognitive safety, making notable strides toward practical, trustworthy robotic systems. With a growing citation record and impactful publications, Yiran Hu is an emerging voice shaping the future of intelligent, tissue-safe robotics.
Research Focus
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Top Papers
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