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Ahmed Iqbal

Ahmed Iqbal

Assistant Professor- Information Systems & Business Analytics (ISBA) College of Business Administration

Contact Details
Job Title
Assistant Professor- Information Systems & Business Analytics (ISBA)
College
College of Business Administration

Dr. Ahmed Iqbal is an Assistant Professor of Information Systems and Data Analytics in the College of Business Administration at A'Sharqiyah University, Oman. He holds a Ph.D. in Computer Science from COMSATS University Islamabad and completed a postdoctoral research fellowship at Hamad Bin Khalifa University (HBKU), Doha, Qatar. His research centres on computer vision, medical imaging, deep learning, and vision transformers, with a growing focus on federated learning. He has published more than 25+ articles in top-tier (Q1) journals including Knowledge-Based Systems, Expert Systems with Applications, and Engineering Applications of Artificial Intelligence with over 1,600+ citations, an h-index of 19, and recognition among the Stanford University & Elsevier World's Top 2% Scientists (2025). Alongside teaching and curriculum development, he supervises student research and leads/co-leads funded projects in artificial intelligence, blockchain, and edge intelligence.

Ph.D. in Computer Science

* Computer Vision,

* Medical Image Analysis,

* Deep Learning,

* Vision Transformers,

* Image Segmentation & Classification,

* Federated Learning,

* Generative Adversarial Networks,

* Explainable AI in Healthcare

Journal paper

2024 Iqbal, A., Usman, M., Ahmed, Z., & Malik, I. (2024). Rethinking encoder-decoder architecture using vision transformer for colorectal polyp and surgical instruments segmentation. Engineering Applications of Artificial Intelligence, 136(B). (IF 8.0; Q1) https://doi.org/10.1016/j.engappai.2024.108962
2023 Iqbal, A., & Sharif, M. (2023). Memory-efficient transformer network with feature fusion for breast tumor segmentation and classification. Engineering Applications of Artificial Intelligence, 127(B). (IF 8.0; Q1) https://doi.org/10.1016/j.engappai.2023.107292
2023 Iqbal, A., & Sharif, M. (2023). BTS-ST: Swin Transformer Network for Segmentation and Classification of Multimodality Breast Cancer Images. Knowledge-Based Systems, 267. (IF 8.1; Q1) https://doi.org/10.1016/j.knosys.2023.110393
2023 Iqbal, A., & Sharif, M. (2023). PDF-UNet: A semi-supervised method for segmentation of breast tumor images using a U-shaped pyramid-dilated network. Expert Systems with Applications, 221. (IF 8.6; Q1) https://doi.org/10.1016/j.eswa.2023.119718
2023 Iqbal, A., Usman, M., & Ahmed, Z. (2023). Tuberculosis chest X-ray detection using CNN-based hybrid segmentation and classification approach. Biomedical Signal Processing and Control, 84. (IF 5.0; Q1) https://doi.org/10.1016/j.bspc.2023.104667
2022 Iqbal, A., Sharif, M., Khan, M. A., Nisar, W., & Alhaisoni, M. (2022). FF-UNet: A U-shaped deep convolutional neural network for multimodal biomedical image segmentation. Cognitive Computation. (IF 4.8; Q1) https://doi.org/10.1007/s12559-022-10038-y
2022 Iqbal, A., Sharif, M., Yasmin, M., Raza, M., & Aftab, S. (2022). Generative adversarial networks and its applications in the biomedical image segmentation: a comprehensive survey. International Journal of Multimedia Information Retrieval. (IF 2.5) https://doi.org/10.1007/s13735-022-00240-x
2022 Iqbal, A., Usman, M., & Ahmed, Z. (2022). An efficient deep learning-based framework for tuberculosis detection using chest X-ray images. Tuberculosis, 136. (IF 2.9) https://doi.org/10.1016/j.tube.2022.102234
2021 Iqbal, A., & Sharif, M. (2021). MDA-Net: Multiscale dual attention-based network for breast lesion segmentation using ultrasound images. Journal of King Saud University – Computer and Information Sciences, 34(9). (IF 13.4; Q1) https://doi.org/10.1016/j.jksuci.2021.10.002

* Member IEEE,

* IEEE Computer Society,

* Serves as a reviewer for 40+ ISI-indexed Journals across IEEE, Elsevier, Springer, Nature, and Wiley