Papers
17
Total Citations
548
H-Index
11
About
Zebing Mao is a pioneering researcher at the intersection of soft robotics, human–robot interaction, and intelligent systems. His work is defined by two complementary threads: advancing the fundamental mechanics of soft actuators and integrating them with cutting-edge artificial intelligence. Mao’s most impactful contribution is his comprehensive review on large language models for human–robot interaction (224 citations), which has become a foundational reference for researchers exploring how AI can enhance robotic communication and task execution. In soft robotics, he has designed innovative fluidic rolling robots, multi-layer dielectric elastomer grippers, and electro-conjugate fluid-driven fingers, demonstrating novel approaches to creating flexible, responsive machines. His recent work applying machine learning to a soft robotic system for studying fecal incontinence (34 citations) exemplifies his commitment to translating engineering into biomedical solutions. With over 500 total citations across his publications, Mao is recognized for his DIY fabrication methods for stretchable sensors and bio-inspired circular actuators. His research not only pushes the boundaries of soft robotic design but also bridges the gap between advanced materials, AI, and real-world medical applications.
Research Focus
Key Achievements
Top Papers
- 1Large language models for human–robot interaction: A review224 citations · 2023
- 2Fluidic rolling robot using voltage-driven oscillating liquid57 citations · 2022
- 3Soft Robotic Gripper Based on Multi-Layers of Dielectric Elastomer Actuators47 citations · 2021
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- 7Novel soft robotic finger model driven by electrohydrodynamic (EHD) pump21 citations · 2024
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