Papers
5
Total Citations
85
H-Index
5
About
Mohamed A. Sehili is a leading researcher in social signal processing and human-robot interaction (HRI), with a specialized focus on the computational understanding of laughter, smiles, and emotional cues. His work lies at the intersection of affective computing and social robotics, where he investigates how robots can detect and respond to human behavioral markers to foster more natural, engaging interactions. A key contribution is his involvement in the Joker project, which pioneered multimodal data collection of humorous interactions, demonstrating that laughter is not merely a reaction but a critical social signal for building rapport and positive atmospheres. His research on cross-corpus experiments with elderly populations is particularly notable, addressing the underexplored area of detecting laughter and emotion in real-life HRI with older adults. With over 85 combined citations, Sehili’s studies on inferring emotional states from speech and behavioral cues have laid foundational methods for making robots socially aware. His work is essential reading for anyone interested in designing empathetic machines that can genuinely connect with humans across diverse age groups and contexts.
Research Focus
Key Achievements
Top Papers
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- 5Smile and Laughter Detection for Elderly People-Robot Interaction5 citations · 2015