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Muhamad Hafiz Abd Latif is a leading researcher in affective computing and human-robot interaction (HRI), specializing in the use of thermal imaging for emotion recognition. His pioneering work focuses on enabling robots to perceive and respond to human emotional states, a critical step toward developing socially intelligent machines. Latif’s most influential contributions center on applying Gray-Level Co-occurrence Matrix (GLCM) features to thermal facial imprints, a novel method that captures physiological cues of affect—such as subtle temperature changes—unlike conventional visual-based systems. His seminal paper, “Implementation of GLCM Features in Thermal Imaging for Human Affective State Detection” (2015), has garnered 33 citations, establishing a foundational approach for non-contact, privacy-preserving emotion detection. Subsequent works, including “Thermal imaging based affective state recognition” (19 citations) and “Emotion detection from thermal facial imprint based on GLCM features” (13 citations), further validate the robustness of this technique. Latif’s research bridges computer vision, machine learning, and robotics, offering a pathway to robots that can genuinely “read” human emotions. His work is particularly notable for its potential in healthcare, assistive robotics, and human-robot collaboration, where accurate affect sensing is paramount. With a cumulative citation impact exceeding 67, Latif continues to shape the future of emotionally aware robotic systems.