Hadiur Rahman Nabil
Bsc. Undergraduate | Computer Science & Engineering (CSE)
Research Assistant
Contact:
Advanced Machine Intelligence Research Lab
(AMIRL), Block-B, Banani.
Dhaka-1213, Bangladesh
E-mail:
hadiurrahmannabil@gmail.comTelephone:
Office:
Cell:
Bachelor of Science
American International University-Bangladesh [ Jan 2020- April 2024]
Computer Science & Engineering
Activities and societies: Competitive programming, Academic Research
Hadiur Rahman Nabil completed his B.Sc. degree in Computer Science and Engineering (CSE) from the American International University-Bangladesh (AIUB) in 2024. During his undergraduate studies, he actively participated in competitive programming, competing in prestigious events such as the ACM International Collegiate Programming Contest (ACM-ICPC) Preliminary and several Intra-University Programming Contests.
He is proficient in multiple programming languages, including C++, Python, R, Java, C#, and PHP, and has hands-on experience with diverse technologies such as TensorFlow, Scikit-learn, NumPy, Pandas, MATLAB, ASP.NET, and MySQL.
Nabil began his professional research journey as a Research Intern at the Advanced Machine Intelligence Research (AMIR) Lab and currently serves as a Research Assistant under the supervision of Dr. M. Firoz Mridha. His research focuses on deep learning, computer vision, and AI applications in healthcare. To date, he has authored multiple peer-reviewed publications, including papers in IEEE, Elsevier, and BMC journals, international conferences, and a book chapter, showcasing his growing contribution to cutting-edge AI research.
| Organization | Position | Duration |
| Advanced Machine Intelligence Research Lab (AMIR Lab) | Research Assistant (Internship) | August 2023 - Present |
| Talent Care Education | Academic Consultant | January 2021 - December 2023 |
1. Atif Ahmed Showrov, Md Tarek Aziz, Hadiur Rahman Nabil, Jamin Rahman Jim, Md Mohsin Kabir, M. F. Mridha, Nobuyoshi Asai, & Jungpil Shin. (2024). "Generative adversarial networks (GANs) in medical imaging: Advancements, applications, and challenges". IEEE Access, 12. DOI: 10.1109/ACCESS.2024.3370848.
2. Hadiur Rahman Nabil, Istyak Ahmed, Aritra Das, M. F. Mridha, Md Mohsin Kabir & Zeyar Aung. (2025). "MSFE-GallNet-X: A Multi-Scale Feature Extraction-based CNN Model for Gallbladder Disease Analysis with Enhanced Explainability". BMC Medical Imaging 25, 360. DOI: https://doi.org/10.1186/s12880-025-01902-y
3. Mir Nafiul Nagib, Rahat Pervez, Afsana Alam Nova, Hadiur Rahman Nabil, Zeyar Aung & M. F. Mridha. (2025). "TuSegNet: A Transformer-Based and Attention-Enhanced Architecture for Brain Tumor Segmentation". IEEE Open Journal of the Computer Society, pp. 1-12. DOI: https://doi.org/10.1109/OJCS.2025.3569758
4. Hashibul Ahsan Shoaib, Hadiur Rahman Nabil, Md Anisur Rahman, Md Mohsin Kabir, M. F. Mridha & Jungpil Shin. (2025). "Advancements and challenges of deep learning architectures for aerial image analysis: A systematic review". Intelligent Systems with Applications, p.200537. DOI: https://doi.org/10.1016/j.iswa.2025.200537
5. MD Azam Khan, Arifur Rahman, Farhad Uddin, Kanchon Kumar Bishnu, Hadiur Rahman Nabil, M. F. Mridha & Md. Jakir Hossen. (2025). "A Physics-Guided Bayesian Neural Network for Sensor Fault Detection in Wind Turbines". IEEE Open Journal of the Computer Society, pp. 1-12. DOI: https://doi.org/10.1109/OJCS.2025.3577588
6. Istyak Ahmed, Hadiur Rahman Nabil, MD. Golam Rabbani Abir, Tazdik Hossain, Aritra Das, & M. F. Mridha . (2024). "NeuroNet: An Attention-Driven Lightweight Deep Learning Model for Improved Brain Cancer Diagnosis." 2024 International Conference on Decision Aid Sciences and Applications (DASA). DOI: 10.1109/DASA63652.2024.10836274
7. Aritra Das, Hadiur Rahman Nabil, Fahad Pathan, Momotaz Rahman Ouishy, M. F. Mridha, & Jungpil Shin. (2024). "Explainable AI-driven vision transformers for assessing fruit freshness via transfer learning." [Accepted in ICCIT]
8. Shahriar Siddique Ayon, Sharia Arfin Tanim, Hadiur Rahman Nabil, Maruful Islam, Tonmoy Mohajan, & Kamruddin Nur. (2024). "Insights into zooplankton abundance dynamics in tropical temporary ponds using machine learning and explainable AI". International Conference on Innovations in Science, Engineering and Technology 2024 (ICISET 2024). DOI: 10.1109/ICISET62123.2024.10939657
9. Hadiur Rahman Nabil, Md Golam Rabbani Abir, Mst Moushumi Khatun, Md Eshmam Rayed, & Md Abdul Hamid. (2024). "Banana leaf spot disease detection using deep learning-based algorithms." [Accepted]
Academic Research Grant
Awarding institution: Competitive Research Fund of The University of Aizu, Japan
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