Miles Eldon
Papers
1
Total Citations
62
H-Index
1
About
Miles Eldon’s research lies at the intersection of human-robot interaction, cognitive science, and natural language processing, with a focus on how robots can interpret human communication in real time. His most cited work, “Interpreting multimodal referring expressions in real time” (2016, 62 citations), explores how humans seamlessly integrate language, gesture, and context to refer to objects—and how robots can replicate this incremental processing to collaborate more effectively on shared tasks. By demonstrating that robots can fuse multimodal cues as they unfold, Eldon has advanced the design of more intuitive and responsive robotic systems. His contributions are particularly impactful for assistive robotics and collaborative manufacturing, where real-time understanding is critical. With over 60 citations on this key paper alone, Eldon’s work is shaping how machines learn to “think on their feet” alongside human partners, bridging the gap between human communication and machine interpretation.
Research Focus
Key Achievements
Top Papers
- 1Interpreting multimodal referring expressions in real time62 citations · 2016