Nojoom A. Alnajem

Papers

Total Citations

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About

Nojoom A. Alnajem is a rising researcher in artificial intelligence and affective computing, with a focus on multi-modal sentiment analysis and human-machine interaction. Her most cited work, "Affective Interaction: Attentive Representation Learning for Multi-Modal Sentiment Classification" (2022, 15 citations), introduces a novel attentive representation learning framework that enhances the ability of AI systems to interpret subjective human attitudes from diverse data streams, including text, audio, and visual cues. This contribution addresses a critical challenge in developing emotionally intelligent machines, such as affective robots and autonomous vehicles, by improving how models capture nuanced user sentiments. Alnajem’s research bridges the gap between raw multi-modal data and meaningful affective understanding, offering practical implications for more responsive and empathetic AI interfaces. Her work has garnered attention for its innovative approach to representation learning, laying groundwork for future advances in context-aware sentiment classification. As an emerging voice in the field, Alnajem continues to explore how attentive mechanisms can deepen machine comprehension of human emotion, positioning her as a promising contributor to the next generation of human-centered AI technologies.