Centre for AI and Digital Health Technology Lab, the University of Queensland (UQ) - Bangladesh
Author Profile
Scopus
🎓 Early Academic Pursuits
Mr. S. M. Masfequier Rahman Swapno began his academic journey with a strong foundation in Computer Science and Engineering (CSE) at the Bangladesh University of Business and Technology (BUBT), where he earned his B.Sc. degree with a commendable CGPA of 3.71/4.00. His academic curiosity led him to explore advanced computational methodologies, culminating in his thesis titled "A Reinforcement Learning Approach to Adaptive Traffic Signal Management," supervised by Md. Shahiduzzaman. This research laid the groundwork for his later endeavors in artificial intelligence, deep learning, and medical imaging technologies.
💼 Professional Endeavors
Mr. Swapno has gained substantial professional experience in artificial intelligence and medical diagnostics, working in prestigious research labs and collaborating with international scholars. He is currently affiliated with the AI and Digital Health Technology Lab at The University of Queensland (UQ), Australia, under the supervision of Dr. Mohammad Ali Moni. Previously, he contributed to the Advanced Machine Intelligence Research Lab in Dhaka, Bangladesh, under the guidance of Dr. Muhammad Firoz Mridha. His work has also led him to collaborate with esteemed professors from Lebanon, Bangladesh, and India on groundbreaking machine learning and deep learning projects.
🌍 Impact and Influence
Mr. Swapno's research has made a profound impact in the fields of machine learning and medical diagnosis. His contributions in artificial intelligence-powered medical imaging have paved the way for more efficient, accurate, and explainable AI models in healthcare. His expertise has influenced researchers and practitioners globally, especially in the areas of brain tumor detection, cancer diagnosis, and disease classification.
His involvement in conferences, such as the IEEE International Conference on Computing and Machine Intelligence (ICMI) 2024, has further amplified his influence. His research on "Performance Improvements of Machine Learning-Based Crime Prediction in Bangladesh" and "A Novel Machine Learning Approach for Fast and Efficient Detection of Mango Leaf Diseases" have been recognized on an international scale.
🏆Academic Cites
Mr. Swapno's publications are widely cited in leading Q1 journals, demonstrating the relevance of his research. His papers in Nature Scientific Reports, IEEE Transactions on Image Processing, and Elsevier’s Medical Image Analysis have collectively accumulated numerous citations, solidifying his position as a rising researcher in AI-driven medical diagnosis.
🌟 Legacy and Future Contributions
Mr. Swapno is committed to advancing the field of medical diagnosis through artificial intelligence. His future contributions will focus on developing hybrid deep learning models for precise and rapid medical imaging solutions. His upcoming work, including "A Novel Ensemble Transformer Model for Fast and Accurate Depression Detection and Severity Analysis with Explainable AI", promises to revolutionize mental health diagnosis.
By continuing to collaborate with leading global researchers, Mr. Swapno aims to push the boundaries of AI-driven medical diagnosis and healthcare technology. His research will contribute to improving patient care, reducing diagnostic errors, and making AI-based medical solutions more accessible worldwide.
Medical Diagnosis
Mr. Swapno’s pioneering work in medical diagnosis has significantly enhanced AI-driven healthcare solutions. His innovative research in medical diagnosis focuses on developing deep learning-based models for brain tumor detection, cancer diagnosis, and sleep disorder classification. With continuous advancements in medical diagnosis, his contributions will shape the future of AI applications in healthcare.
📝Notable Publication
📝Accelerated and precise skin cancer detection through an enhanced machine learning pipeline for improved diagnostic accuracy
Authors: S.M. Masfequier Rahman Swapno, S.M. Nuruzzaman Nobel, P.K. Meena, J. Bahadur, A. Appaji
Journal: Results in Engineering
Year: 2025
Citations: 0