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About

Amir Shabani is a leading researcher at the intersection of affective computing, social robotics, and edge AI, with a focused mission to enhance the quality of life for older adults. His work pioneers the integration of augmented reality and emotion AI on edge devices, enabling social companion robots to become more empathetic and responsive companions for independent living. Shabani’s major contributions include developing fine-grained speech emotion recognition models and improved deep convolutional neural networks for facial emotion recognition, specifically addressing the critical gap in age-diversified datasets that often exclude seniors over fifty. His most cited paper, "Augmented Reality and Affective Computing on the Edge Makes Social Robots Better Companions for Older Adults" (2021, 12 citations), demonstrates the practical impact of his research in long-term care settings. With additional influential works on social embodiment in smart spaces and age-augmented FER, Shabani has established himself as a key innovator in creating emotionally intelligent, context-aware robotic systems that foster meaningful human-robot interactions for vulnerable populations.