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About

Shervin Emami is a robotics researcher whose work sits at the intersection of human-robot interaction, social robotics, and autonomous systems. He is best known for his pioneering FaceBots project, a series of influential studies exploring how robots can forge meaningful, long-term relationships with humans by integrating face recognition, natural language dialogue, and real-time social media data drawn from platforms like Facebook. This innovative approach addressed a well-documented challenge in the field: that human interest in robots tends to wane after weeks of interaction. By enabling robots to remember, learn from, and socially engage with individuals over extended periods, Emami's FaceBots work — accumulating over 50 citations across multiple publications — pushed the boundaries of what sustained human-robot relationships could look like. Beyond social robotics, Emami has contributed to developmental robotics, investigating how boredom-driven, self-directed learning can help robots adapt intelligently to complex real-world environments. His earlier work also tackled the practical challenges of long-term autonomous robot operation, developing web-based frameworks that allowed untrained users to interact with sophisticated mobile robots remotely. Together, his research paints a picture of a scientist deeply committed to making robots more socially intelligent, adaptive, and genuinely useful companions.