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About

Siti Norul Huda Sheikh Abdullah is a Malaysian computer scientist whose research spans computer vision, autonomous robotics, and technology-enhanced learning. With expertise rooted in artificial intelligence and machine learning, she has made significant contributions to both applied robotics systems and intelligent image processing. Her most impactful work, "Underwater Fish Detection and Counting Using Mask Regional Convolutional Neural Network" (2022, 60 citations), demonstrates her ability to bridge deep learning techniques with real-world aquaculture challenges, offering a scalable solution to automated fish farming management. This work highlights her strength in applying convolutional neural architectures to domain-specific problems. Abdullah has also advanced the field of robotics education, exploring how computational and adversarial thinking can be cultivated through experiential learning frameworks, a timely contribution in the era of Industry 4.0. Her earlier research laid important groundwork in simultaneous localization and mapping (SLAM), humanoid robot localization, and multi-agent robot soccer strategy, demonstrating a career-long commitment to intelligent autonomous systems. Through camera calibration, video stabilization, and multi-modal robot vision research, she has consistently pushed the boundaries of robot perception. Her cumulative scholarly influence, spanning over a decade of publication and more than 120 citations, marks her as a versatile and enduring contributor to intelligent systems research.