Papers
16
Total Citations
421
H-Index
7
About
Kevin Lee is a robotics and human-robot interaction researcher whose work spans natural language processing, augmented reality communication, and assistive robotics. He is perhaps best known for the "Tell Me Dave" project, which pioneered context-sensitive grounding of natural language commands to robotic manipulation tasks — recognizing that even simple instructions like "boil water" require robots to dynamically interpret their environment. This foundational work has accumulated over 250 citations across its 2014 and 2015 publications, establishing Lee as a key contributor to language-guided robot control. A significant thread of Lee's research addresses the challenge of effective human-robot teaming in unstructured field environments. His series of augmented reality studies demonstrates how AR interfaces and gesture control can dramatically improve situational awareness and information exchange between human operators and autonomous robots, collectively attracting nearly 100 citations since 2018. His work on assistive robotics further broadens his impact, exploring activity learning systems using RGB-depth sensors to support ambient assisted living applications, as well as emotionally intelligent companion robots. Together, Lee's portfolio reflects a consistent mission: making robots more intuitive, communicative, and genuinely useful partners for humans across diverse real-world settings.
Research Focus
Key Achievements
Top Papers
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- 3Come See This! Augmented Reality to Enable Human-Robot Cooperative Search49 citations · 2018
- 4Human activity learning for assistive robotics using a classifier ensemble35 citations · 2018
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- 6Augmented Reality for Human-Robot Teaming in Field Environments16 citations · 2019
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- 8Automation With Intelligence in Drug Research7 citations · 2019
- 9An assigned responsibility system for robotic teleoperation control7 citations · 2018
- 10Human Emotional Understanding for Empathetic Companion Robots6 citations · 2016