Research & Publications
Research interests
AI-assisted cancer detection and classification; medical imaging and computational pathology; deep learning and computer vision; multi-scale representation learning; attention-based feature fusion; explainable AI; model robustness, validation, and generalization.
Proposed research: Exploring deep-learning and hybrid architectures for cancer detection and medical image classification across histopathology and radiological images. This is an emerging research agenda, with no experimental results claimed.
Journal publications
- Faruk, M. I., et al. (including Md Nazmussakib). “Channel attention recalibrated fusion of CoAtNet and frozen DINOv2 features for binary chest X ray classification.” Discover Computing, 29, 551. DOI
- Meruga, V. B., et al. (including Md Nazmussakib). “Edge–Cloud Digital Service Loop Framework for Real-Time Cardiac Patient Monitoring and Predictive Intervention in IoT-Enabled Healthcare Systems.” IEEE Internet of Things Magazine, accepted article. DOI
- Bakhsh, M. M., et al. (including Md Nazmussakib). “CAUSAL artificial intelligence and data-driven decision intelligence in personalized medicine: a review of healthcare informatics systems.” Personalized Medicine, 23(4), 383–410. DOI
- Adnan, M., et al. (including Md Nazmussakib). “Interpretable Data Analytics for One-Year Diabetes Progression: Comparative Prediction, Feature Reliance, and Ranking Stability.” European Journal of Medical and Health Research, 2(6), 257–269. DOI
- “AI-Powered Business Intelligence: Enhancing Decision-Making through Predictive Analytics and Big Data.” Posthumanism, 6(3), 218–237 (2026). DOI
Conference papers
- Das, N., et al. (including Md Nazmussakib). “Four Class Brain Tumor Classification in MRI Using Multi Scale Attention Guided Feature Fusion Network.” IEEE Technology and Innovation Conference. DOI
- Nazmussakib, M., et al. “Adversarial Machine Learning for Robust Cyber Defense Systems.” IEEE ICCTWC. DOI
- Rozario, E., et al. (including Md Nazmussakib). “Dynamic Big Data Summarisation Using Transformer-Based Generative Models.” IEEE I3CTCON. DOI
- “Decision Robustness under Information Noise: A Machine Learning Perspective on Managerial Decision Systems.” IEEE CICN (2026). DOI
- “Data-Driven Operations and Supply Chain Management Using Large Language Models.” IEEE CICN (2026). DOI
Certifications
Google Data Analytics Professional Certificate; Tableau 2024 A–Z (Udemy); Power BI Business Intelligence (Udemy); Google Analytics.