Md Sabbir Hossain
M.Sc. in Computer Science
Researcher
Contact:
Advanced Machine Intelligence Research Lab
(AMIRL), Block-B, Banani.
Dhaka-1213, Bangladesh
E-mail:
sabbirmdh1991@gmail.comTelephone:
Office:
Cell:
Master’s in Computer Science, Western Illinois University, Macomb, IL 61455, USA
MD SABBIR HOSSAIN is currently pursuing an MS in Computer Science at the School of Engineering and Technology, Western Illinois University, Illinois, United States. His research interests lie in deep learning and computer vision, with a particular focus on applying advanced deep learning techniques to spinal cord MRI analysis. He is also actively exploring multimodal deep learning approaches for machine failure risk prediction and developing automatic navigation systems and self-driving technology for agricultural machinery.
Hossain, M. S., Rahman, M., Rahman, A., Kabir, M. M., Mridha, M. F., Huang, J., & Shin, J. (2025). Automatic navigation and self-driving technology in agricultural machinery: A state-of-the-art systematic review. IEEE Access.
Rahman, M., Hossain, M. S., Rozario, U., Roy, S., Mridha, M. F., & Dey, N. (2025). Multisensenet: multi-modal deep learning for machine failure risk prediction. IEEE Access.
Hossain, M. S., Rahman, M., Ahmed, M., Rahman, A., Kabir, M. M., Mridha, M. F., & Shin, J. (2025). An in-depth review and analysis of deep learning methods and applications in spinal cord imaging. Healthcare Analytics, 100429.
Hossain, M. S., Rahman, M., Ahmed, M., Kabir, M. M., Mridha, M. F., & Shin, J. (2024, November). Deeplabv3att: Integrating attention mechanisms in deeplabv3 for enhanced road segmentation. In 2024 International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies (3ICT) (pp. 711-718). IEEE.
Rahman, M., Hossain, M. S., Eva, A. A., Kabir, M. M., Mridha, M. F., & Shin, J. (2024, November). Alzheimers disease classification with a hybrid cnn-svm approach on enhanced mri data. In 2024 International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies (3ICT) (pp. 50-57). IEEE.
Hossain, M. S., Rahman, M., Abir, M. G. R., Maua, J., & Rahman, A. (2025). Plant leaf disease detection using deep stacking: integrating cnns and gradient boosting for enhanced classification accuracy. In Machine Vision in Plant Leaf Disease Detection for Sustainable Agriculture (pp. 15-26). Singapore: Springer Nature Singapore.
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