James F. Mullen
University of Maryland, College Park, Virginia Tech, Amazon (United States)
Papers
4
Total Citations
111
H-Index
3
About
James F. Mullen is pioneering the next generation of intelligent home robots—machines that don’t just follow commands but truly understand your world. His research sits at the intersection of embodied AI, human-robot interaction, and large language models (LLMs), with a focus on enabling robots to navigate, reason, and communicate in human-centric environments. Mullen’s most influential work, “Can an Embodied Agent Find Your ‘Cat-shaped Mug’?” (2023, 70 citations), introduces LGX, a zero-shot object navigation algorithm that uses LLMs to guide robots toward uniquely described targets in unfamiliar spaces—a leap toward truly helpful home assistants. He also developed methods for transparent human-robot collaboration, using passive augmented reality and active haptic feedback to communicate a robot’s inferred goals (2021, 34 citations), ensuring humans stay in the loop. Most recently, his 2024 work on anomaly detection equips robots to spot dangerous or unsanitary situations, like leaving milk out or the stove on, and alert their users. By blending language understanding with physical action, Mullen is redefining what it means for a robot to be a trusted, proactive partner in everyday life.
Research Focus
Key Achievements
Top Papers
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