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About

Cigdem Beyan is a leading researcher at the intersection of computer vision, affective computing, and social robotics, with a focus on decoding the subtle nuances of human nonverbal communication. Her work is pivotal in advancing how machines perceive and respond to human emotions and social signals, particularly in human-robot interaction (HRI) and healthcare settings. A major contribution is her pioneering research on **vitality forms**—the dynamic variations in how actions are performed that convey attitudes and intentions—where she has developed diffusion-based unsupervised pre-training models for automated recognition. Beyan has also made significant strides in **facial emotion recognition (FER)** , notably addressing the real-world challenge of occluded faces (e.g., by masks) through her work on transfer learning from unsupervised pre-training. Her research has direct applications in **gerontological healthcare**, where she explores the use of socially pertinent robots. With papers accumulating citations and appearing in top venues, Beyan’s work is foundational for building more perceptive, socially intelligent agents capable of natural and empathetic interaction, bridging the gap between human-human and human-robot social dynamics.