Syamimi Abdul-Khalil

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About

Syamimi Abdul-Khalil is a researcher whose work lies at the intersection of artificial intelligence, autonomous systems, and human-robot interaction. Her primary research focus is on object detection for autonomous mobile robots (AMRs), a critical area that enables robots to perceive, navigate, and interact safely with dynamic environments. Her most-cited paper, a comprehensive 2023 review on object detection for AMRs, has already garnered 10 citations, reflecting its timely relevance as industries increasingly adopt AI-driven mobile platforms. In this work, Abdul-Khalil synthesizes advances in computer vision and deep learning, highlighting how robust detection systems are foundational to the development of human-interaction systems. Her contributions underscore the importance of bridging perception and action in robotics, particularly for applications in manufacturing, logistics, and service sectors. By addressing challenges such as real-time processing and environmental variability, she provides a roadmap for safer, more intelligent autonomous navigation. Abdul-Khalil’s research is shaping the next generation of mobile robots that work closely alongside humans, making her a notable voice in the evolving landscape of embodied AI.