Yi Dai
Papers
2
Total Citations
14
H-Index
2
About
Yi Dai is a pioneering researcher at the intersection of human-robot interaction and end-user programming, with a core focus on making service robots accessible to non-experts. Her work addresses the critical challenge of bridging the gap between complex robotic systems and everyday users. Dai’s major contributions include developing intuitive visual representations of knowledge graphs that enable service robots to communicate situational awareness, and pioneering the use of Large Language Models (LLMs) as engines for end-user robot programming. Her 2021 paper on knowledge graph patterns (9 citations) laid foundational work for robot-to-human communication, while her 2024 "Cocobo" study (5 citations) represents a breakthrough in natural language programming, tackling the persistent challenges of user expression space and debugging limitations. These contributions are particularly notable for their practical orientation—Dai’s research doesn’t just advance theory but creates tangible tools that empower non-programmers to customize robot behaviors. Her work is increasingly influential in the growing field of accessible robotics, where her insights into LLM-driven programming are helping shape the next generation of user-friendly robotic systems.
Research Focus
Key Achievements
Top Papers
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- 2