Nabiha Asghar
Papers
1
Total Citations
11
H-Index
1
About
Nabiha Asghar is a researcher at the intersection of artificial intelligence, social robotics, and human-robot interaction. Her work focuses on developing computational frameworks that enable autonomous agents to reason about and align with human social and emotional norms. Asghar’s most cited paper, “Monte-Carlo Planning for Socially Aligned Agents using Bayesian Affect Control Theory” (2014, 11 citations), introduces a novel approach that integrates Affect Control Theory—a mathematically rigorous model predicting the affective content of human actions based on empirical data—with Bayesian inference and Monte-Carlo planning. This work allows agents to anticipate and adapt to human affective responses, making them more socially aware and trustworthy. By grounding machine decision-making in normative human behavior statistics, Asghar advances the field of socially aligned AI, addressing critical challenges in human-robot collaboration. Her contributions are particularly notable for bridging formal social science models with practical planning algorithms, offering a pathway toward machines that can navigate complex social environments. With growing recognition, Asghar’s research continues to influence how autonomous systems perceive and respond to human affect, promising safer and more intuitive interactions in applications from healthcare to service robotics.
Research Focus
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Top Papers
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