Dr. Md. Akizur Rahman is a Casual Lecturer in Information Technology at KOI. He completed his PhD in Computer Science and Engineering at the University of New South Wales (UNSW Sydney), Australia. His research focuses on artificial intelligence, machine learning, deep learning, computer vision, and medical image analysis, with an emphasis on developing AI-driven solutions for computer-aided diagnosis using 2D and 3D medical imaging. He has teaching experience as a Casual Lecturer and Tutor at the University of New South Wales (UNSW Sydney), where he taught courses in machine learning, data mining, computer vision, and deep learning. He also served as a Research Assistant and contributed to teaching and research activities at Universiti Kebangsaan Malaysia (UKM). His research has been published in leading international journals and conferences.

Rahman, M. A., Singh, S., Iyer, S., et al. (2024). Sigmoid Colon Localisation for Acute Diverticulitis Disease Using SigLoc 3D Convolution Neural Network. MICAD, Springer. Best Paper Award.

Rahman, M. A., Singh, S., Shanmugalingam, K., et al. (2023). Attention and Pooling Based Sigmoid Colon Segmentation in 3D CT Images. DICTA, IEEE.

Rahman, M. A., Chandren Muniyandi, R., Albashish, D., Rahman, M. M., & Usman, O. L. (2021). Artificial Neural Network with Taguchi Method for Robust Classification Model to Improve Classification Accuracy of Breast Cancer. PeerJ Computer Science, 7, e344.