Shahira Ali
Papers
2
Total Citations
28
H-Index
2
About
Shahira Ali investigates how people perceive and interact with social robots, focusing on the critical intersection of robot capabilities and human expectations. Her research explores how factors like language fluency, task competency, and even humor shape user trust and engagement with robotic partners. In her highly cited 2022 work, “Who’s Laughing NAO? Examining Perceptions of Failure in a Humorous Robot Partner” (26 citations), Ali demonstrated that a robot’s use of humor can significantly alter how users respond to its mistakes—a key insight for designing more resilient and socially fluent machines. Her 2024 paper, “What Am I? Evaluating the Effect of Language Fluency and Task Competency on the Perception of a Social Robot,” further unpacks how a robot’s verbal polish and reliability jointly influence whether it is seen as competent or uncanny. By systematically testing these variables with human participants, Ali provides actionable guidance for engineers building robots destined for homes, schools, and hospitals. Her work is essential reading for anyone interested in human-robot interaction, affective computing, or the design of socially intelligent agents that can gracefully navigate failure.
Research Focus
Key Achievements
Top Papers
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- 2