BUBT Logo
BUBT Logo
BUBT Research Graduate School

Hadiur Rahman Nabil

Research Assistant — BUBT Research Graduate School

Hadiur Rahman Nabil

Research Assistant

Email: hadiurrahmannabil@bubt.edu.bd

Blood Group: B+

  • google-scholar
  • research-gate
  • BUBT Logo

Professional Summary

Hadiur Rahman Nabil is a graduate of the American International University–Bangladesh (AIUB) with a strong academic and research background in Artificial Intelligence (AI), Deep Learning, Machine Learning, and Computer Vision. He previously worked as a Research Assistant at the Advanced Machine Intelligence Research (AMIR) Lab, where he contributed to research projects focused on developing intelligent systems for real-world applications. His research interests span AI-driven solutions in healthcare, medical image analysis, pattern recognition, and data-driven decision-making. Through his work, he aims to leverage cutting-edge computational techniques to address complex challenges across diverse domains and create technologies that deliver meaningful societal impact. Nabil is passionate about advancing the frontiers of AI research and translating innovative ideas into practical solutions that improve lives. His long-term goal is to contribute to the development of responsible and impactful artificial intelligence technologies that support scientific progress and the betterment of humanity.

Education

Bachelor of Science (B.Sc. Hons)

Major: Computer Science & Engineering

Institute: American International University Bangladesh

Passing Year: 2024

Academic Experience

Institute Department Position Year

Professional Experience

Institute Department Position Year

Journal Papers

Rufaida Mamun, MD Shalim Sadman, Hadiur Rahman Nabil, M. F. Mridha & Md Mohsin Kabir, "Transforming Sentiment Analysis with Generative AI: A Deep Dive into Modern Techniques and Challenges, " In: Multimedia Tools & Applications, 219 85 (2026-01-01) . 10.1007/s11042-026-21390-8
Hadiur Rahman Nabil , Fariya Sultana Prity , Mohammad Mahmudul Hasan , M.F. Mridha, "An interpretable deep learning framework for multi-scale diagnosis of gastrointestinal conditions across adult and pediatric populations, " In: Computer Methods and Programs in Biomedicine Update, 100252 (2026-01-01) . 10.1016/j.cmpbup.2026.100252

AWARDS AND RESEARCH GRANTS

Award Title Organization Award year Awardee Position Award Description