Niloofar Zarei

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About

Niloofar Zarei is a researcher in computer vision and affective computing, with a focused expertise in automatic facial expression recognition—a cornerstone of human-computer interaction, social robotics, and behavioral monitoring. Her work centers on developing anatomically informed graph-based models to decode human emotions from facial cues, addressing one of the most challenging problems in intelligent systems. In her most-cited paper, "Facial expression recognition using anatomy based facial graph" (2014, 18 citations), Zarei introduced a novel framework that leverages facial anatomy to enhance the accuracy and robustness of emotion detection, bridging the gap between biological structure and computational analysis. This contribution has implications for interactive multimedia and social signal processing, where machines must interpret subtle human expressions. Her subsequent work, "Facial Expression Recognition Using Facial Graph" (2015, 4 citations), further refines these graph-based approaches. Zarei’s research stands at the intersection of pattern recognition and human-centered AI, offering practical tools for more empathetic and responsive technologies. Her work continues to inspire advances in how machines perceive and respond to human emotional states.