Norah Alnaim

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About

Dr. Norah Alnaim has established herself as a leading voice at the intersection of computer vision, human-robot interaction, and assistive technology. Her research focuses on developing intelligent, vision-based systems that bridge the gap between human motion and machine understanding, with a particular emphasis on applications for rehabilitation and inclusive design. Her most influential work, "Hand Gesture Recognition Using Convolutional Neural Network for People Who Have Experienced A Stroke" (2019, 28 citations), exemplifies her commitment to creating accessible interfaces. In this study, Dr. Alnaim pioneered a CNN-based framework that accurately detects and interprets hand gestures, enabling intuitive, non-verbal communication between stroke survivors and robotic or digital devices. By addressing the critical need for usable interfaces in post-stroke rehabilitation, her work has laid a foundation for more responsive assistive technologies that empower individuals with motor impairments. Dr. Alnaim’s contributions are not only technically robust—leveraging deep learning for real-time gesture recognition—but also deeply human-centered, demonstrating how advanced computer vision can restore agency and improve quality of life. Her research continues to inspire new directions in inclusive human-robot collaboration and healthcare robotics.