Papers
9
Total Citations
313
H-Index
8
About
Rui Fang’s research lies at the intersection of human-robot interaction, situated dialogue, and natural language grounding, with a focus on bridging perceptual mismatches between humans and robots in shared physical environments. Her major contributions include pioneering collaborative models for referential communication, such as embodied referring expression generation and probabilistic labeling, which enable robots to dynamically align their representations with human partners. Her most-cited work, “Collaborative effort towards common ground in situated human-robot dialogue” (75 citations), and its follow-up studies (67 and 60 citations) demonstrate how conversation partners mediate differences in visual perception through graph-based representations and iterative grounding. Fang’s impact is evident in over 300 total citations, with her 2012 study on mediating shared perceptual bases (42 citations) laying foundational insights for adaptive dialogue systems. Notably, her 2014 work on perceptive feedback for natural language control integrates high-level planning with low-level robotic control, advancing practical applications in human-robot collaboration. By systematically addressing the challenge of misaligned world models, Fang has shaped how researchers design robots that communicate fluidly and intuitively with humans in real-world settings.
Research Focus
Key Achievements
Top Papers
- 1Collaborative effort towards common ground in situated human-robot dialogue75 citations · 2014
- 2Collaborative Language Grounding Toward Situated Human‐Robot Dialogue67 citations · 2016
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- 4Towards mediating shared perceptual basis in situated dialogue42 citations · 2012
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- 8Perceptive feedback for natural language control of robotic operations10 citations · 2014
- 9Modelling and Analysis of Natural Language Controlled Robotic Systems7 citations · 2014