Suhaila Mohammed

Papers

Total Citations

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About

Suhaila Mohammed is a leading researcher in affective computing, specializing in emotion recognition for human-robot interaction (HRI). Her work bridges artificial intelligence, graph mining, and signal processing to enable machines to perceive and respond to human emotions. In her highly cited 2019 study, "A novel facial emotion recognition scheme based on graph mining" (53 citations), she pioneered the use of graph-based feature extraction to capture subtle facial expressions, significantly improving recognition accuracy. Her comprehensive 2021 survey on emotion recognition for HRI (25 citations) has become a foundational reference for researchers designing emotionally intelligent robots. Mohammed further expanded the field into multimodal analysis, developing innovative techniques for speech emotion recognition using MELBP variants of spectrogram images (2020, 8 citations), addressing the challenge of effective feature selection from audio signals. Her contributions are critical for advancing social robotics, conversational agents, and assistive technologies. By integrating graph theory with emotion detection, Mohammed has opened new pathways for creating more natural, empathetic human-machine interactions, making her work essential reading for students and researchers in affective computing and HRI.