1.An explainable multi-class brain tumor classifier using efficientnetv2 with hybrid attention
mechanisms; Accepted at 2nd IEEE Conference on Computing Applications and Systems (COMPAS
2025),Under Review, 2025.

2. S.Sobhan,A.Zami, M.Ahmed,T. M.Zihan, T. A. Khan, and A. Saha, “A multi-stage deep learning
approach to tuberculosis detection with explainable insights,” in 2025 2nd International Conference on
Next-Generation Computing, IoT and Machine Learning (NCIM), 2025, pp. 1–6. doi
10.1109/NCIM65934.2025.11159991.

3 A.Zami,S.Sobhan, T. M.Zihan, M. Ahsan, F. Rahman, and M. Ahmed, "A lightweight framework for
facial emotion recognition Leveraging geometrical priors with spatial features," in 2025 2nd
International Conference on Next-Generation Computing, IoT and Machine Learning (NCIM), 2025,
pp. 1–6.doi 10.1109/NCIM65934.2025.11160006.

4 A.Zami,R.Islam, T. M. Zihan, and M. Ahmed, "Risk minimization by early readmission prediction for
diabetes patients A data-driven machine learning approach," in 2024 IEEE International Conference on
Biomedical Engineering, Computer and Information Technology for Health (BECITHCON), 2024,
pp. 18–22. doi 10.1109/BECITHCON64160.2024.10962574.

5. T.M.Zihan,A.Zami,M.Ahmed,R.Islam, and F. Ahmed, "From pixels to diagnosis Convolutional
neural networks in tuberculosis screening," in 2024 6th International Conference on Electrical
Engineering and Information Communication Technology (ICEEICT), 2024, pp. 1187–1192. doi
10.1109/ICEEICT62016.2024.10534341

“Lightweight deeplabv3 A computational efficient model for colonoscopy polyp segmentation,” Thesis
Book, 2025.