Behnaz Nojavanasghari
Papers
1
Total Citations
117
H-Index
1
About
Behnaz Nojavanasghari is a leading researcher in affective computing and multimodal machine learning, with a focus on bridging the gap between human emotional expression and artificial intelligence. Her work centers on automatic emotion recognition, particularly in children—a population often overlooked in affect-sensitive technology. Her landmark paper, "EmoReact: a multimodal approach and dataset for recognizing emotional responses in children" (2016), has garnered over 117 citations and introduced a pioneering dataset that enables the development of social robots, affect-aware tutors, and human-computer interaction systems tailored to younger users. By combining audio, visual, and physiological signals, Nojavanasghari’s research advances the robustness of emotion recognition models, addressing challenges like spontaneous expressions and developmental differences. Her contributions have significant implications for mental health monitoring, educational technology, and assistive robotics. Recognized for her innovative use of multimodal data, she continues to shape how machines perceive and respond to human affect, making her work essential reading for students and researchers in affective computing, human-robot interaction, and child-computer interaction.
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Top Papers
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