Rabia Shakoor
Papers
1
Total Citations
3
H-Index
1
About
Rabia Shakoor’s research lies at the intersection of cognitive robotics and computational linguistics, with a particular focus on how robots can ground abstract language in physical experience. Her most-cited work, “Theoretical accounts to practical models: Grounding phenomenon for abstract words in cognitive robots” (2016), bridges high-level theory and implementable models, offering a framework for enabling machines to understand and use abstract concepts—such as emotions or quantities—through sensorimotor interactions. This contribution is pivotal for advancing human-robot communication, moving beyond concrete commands to more nuanced, context-aware dialogue. Though early in her career, with 3 citations on this key paper, Shakoor’s work has already influenced discussions in embodied cognition and artificial intelligence. Her approach synthesizes insights from psychology, linguistics, and robotics, making her a promising voice in the quest for truly intelligent, language-capable machines. For students and researchers, Shakoor’s research offers a clear pathway from theoretical grounding to practical robotic systems, highlighting the ongoing challenge of making AI not just functional, but conceptually rich.
Research Focus
Key Achievements
Top Papers
- 1