My research focuses on signal processing, deep learning, and explainable AI with applications in wireless networks, medical imaging, IoT sensor networks, and intelligent systems. I address challenges in next-generation wireless communications, including millimeter-wave propagation, atmospheric interference, and signal quality optimization, while exploring how artificial intelligence and machine learning can enhance wireless system performance, network optimization, and propagation prediction.
Journal articles
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K. M. Sujon, R. Hassan, K. Choi, M. A. Samad, et al., "Accuracy, precision, recall, f1-score, or MCC? empirical evidence from advanced statistics, ML, and XAI," Journal of Big Data 12:268 (2025), doi:
10.1186/s40537-025-01313-4Metrics guide our choice— / F1, MCC, or accuracy? / Evidence speaks truth. -
Kakon, S. Chakrabarty, Z. Al Sazid, I. A. Begum, M. A. Samad, A. S. M. S. Hosen, "Explainable Deep Ensemble Meta-Learning Framework for Brain Tumor Classification," Cancers 17(17):2853 (2025), doi:
10.3390/cancers17172853Deep nets learn to see— / Tumors revealed, explained clear, / Trust through transparency. -
P. Sarker, A. Ksibi, M. M. Jamjoom, K. Choi, A. A. Nahid, M. A. Samad, "Breast cancer prediction with feature-selected XGB classifier, optimized by metaheuristic algorithms," Journal of Big Data 12:78 (2025), doi:
10.1186/s40537-025-01132-7Features refined well— / XGBoost learns cancer signs, / Early hope prevails. -
P. Sarker, K. Choi, A. A. Nahid, M. A. Samad, et al., “CatBoost with physics-based metaheuristics for thyroid cancer recurrence prediction,” BioData Mining 18:84 (2025), doi:
10.1186/s13040-025-00494-1Thyroid risk returns / Physics guides machine learning— / Recurrence revealed. -
K. M. Sujon, R. B. Hassan, Z. T. Towshi, M. A. Othman, M. A. Samad, K. Choi, "When to Use Standardization and Normalization: Empirical Evidence From ML Models," IEEE Access 12:135300-135314 (2024), doi:
10.1109/ACCESS.2024.3462434Scale or standardize? / Data transformed with purpose— / Models learn better. -
K. A. Alavee, M. H. Zillanee, M. Mostakim, M. A. Samad, et al., "Enhancing Early Detection of Diabetic Retinopathy Through Deep Learning and XAI," IEEE Access (2024), doi:
10.1109/access.2024.3405570Eyes reveal disease— / Deep learning spots early signs, / Vision preserved well. -
M. A. Samad, D.-Y. Choi, K. Choi, "Path loss measurement and modeling of 5G network in emergency indoor stairwell," PLOS ONE 18(3):e0282781 (2023), doi:
10.1371/journal.pone.0282781Signals climb the stairs— / Emergency paths measured, / 5G finds its way. -
M. A. Samad, S.-W. Choi, C.-S. Kim, K. Choi, "Wave Propagation Modeling Techniques in Tunnel Environments: A Survey," IEEE Access 11:2199-2225 (2023), doi:
10.1109/ACCESS.2022.3233877Waves through tunnels flow— / Models guide the signal path, / Underground connects. -
M. A. Samad, F. D. Diba, D.-Y. Choi, "A survey of rain fade models for earth–space telecommunication links," Remote Sensing 13(10):1965 (2021), doi:
10.3390/rs13101965Rain dims the signal— / Models predict fade and loss, / Links stay reliable.