Nazri Mohd Nawi

Tun Hussein Onn University of Malaysia, Universiti Teknologi MARA

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About

Nazri Mohd Nawi is a prominent researcher whose work bridges artificial intelligence, agricultural technology, and robotics. His key research areas include deep learning, computer vision, and automation systems, with a strong emphasis on practical, real-world applications. One of his most notable contributions is the development of a "Real-Time Wheat Classification System for Selective Herbicides Using Broad Wheat Estimation in Deep Neural Networks" (2019), which addresses the critical challenge of automating seed identification in agriculture. This work, garnering 12 citations, offers a technically and economically viable solution for the agricultural industry by leveraging big data and deep learning to replace slow, manual seed identification processes. In the field of robotics, Nawi has also made significant strides with his work on "Robot arm simulation using 3D software application with 3D modeling, programming and simulation support" (2016), where he introduced a novel robotics simulator built on Blender 3D and Python. This simulator, featuring six degrees of freedom, enables smooth, realistic arm movements for pick-and-place tasks. Through these contributions, Nawi demonstrates a clear commitment to advancing automation and intelligent systems, making his research highly relevant for students and researchers interested in the intersection of AI, agriculture, and robotics.