Md Moinul Azim
Md Moinul Azim
Moinul Azim is a Computer Science and Engineering graduate from Bangladesh University of Engineering and Technology (BUET). His research background centers on medical image segmentation, where he conducted a comparative study of different U-Net architectures to segment femur bone structures from QCT scans. His work focused on improving segmentation accuracy using deep learning and evaluating models with metrics such as Dice Coefficient, mIoU, Sensitivity, and Average Precision.
Alongside research, he has worked on multiple data science and machine learning projects, including heart disease prediction, seasonal water quality forecasting, water potability classification, and global pandemic data visualization. He has hands-on experience with Python, data preprocessing, model evaluation, and analytical dashboards in Power BI and Tableau. He is passionate about machine learning, computer vision, and data-driven problem solving, and he is always looking for opportunities to contribute to meaningful projects, collaborate with curious minds, and continue learning.