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About

Nazreen Rusli is a pioneering researcher at the intersection of affective computing, human-robot interaction (HRI), and assistive robotics, with a particular focus on children with Autism Spectrum Disorder (ASD). Her work has garnered over 85 citations, establishing her as an influential voice in developing emotionally intelligent robotic systems. Rusli’s major contributions include the innovative use of thermal imaging and GLCM (Gray-Level Co-occurrence Matrix) features to non-invasively detect human affective states, a breakthrough that enables robots to recognize emotions without contact-based sensors. Her most cited paper, “Implementation of GLCM Features in Thermal Imaging for Human Affective State Detection” (33 citations), laid the groundwork for this approach, followed by “Thermal imaging based affective state recognition” (19 citations) and “Emotion detection from thermal facial imprint based on GLCM features” (13 citations). She also advanced child-specific applications with “Mean of Correlation Method for Optimization of Affective States Detection in Children” (9 citations). Notably, Rusli’s research extends to robotic intervention for ASD children, as seen in “Robot Selection in Robotic Intervention for ASD Children” (6 citations) and “Modules of Interaction for ASD Children Using Rero Robot (Humanoid)” (5 citations), where she explores how humanoid robots can improve social interaction and communication skills. Her work promises to make robots more empathetic and effective partners in therapeutic and everyday settings.