Michael Murray
Papers
5
Total Citations
165
H-Index
4
About
Michael Murray is a robotics and human-robot interaction researcher whose work bridges the gap between artificial intelligence and real-world robotic applications. His research spans three interconnected domains: embodied navigation, social robotics, and robotic manipulation. Murray's most influential contribution is his work on Cooperative Vision-and-Dialog Navigation (2019, 119 citations), which introduced a landmark dataset enabling robots to navigate photorealistic home environments by engaging in natural language dialogue with humans — a foundational step toward socially intelligent autonomous agents. Building on this, his 2022 work on natural language instruction-following for mobile manipulator robots (26 citations) demonstrated how robots can integrate unconstrained language semantics with egocentric visual perception to accomplish household tasks. Murray has also made meaningful strides in social robotics, exploring backchanneling behaviors and self-disclosure interactions as mental health interventions for adolescents, reflecting a commitment to human-centered AI design. His more recent work on learning to grasp in cluttered environments addresses pressing industrial automation challenges. Across his portfolio, Murray consistently tackles problems at the frontier of language, perception, and physical interaction — making his research highly relevant to students interested in embodied AI, assistive robotics, and human-robot collaboration.
Research Focus
Key Achievements
Top Papers
- 1Vision-and-Dialog Navigation119 citations · 2019
- 2
- 3
- 4Tell Me About It7 citations · 2023
- 5Learning to Grasp in Clutter with Interactive Visual Failure Prediction3 citations · 2024