Mahmud Naeem
Lecturer
Mahmud Naeem is a Lecturer in the Department of Computer Science and Engineering (CSE) at Bangladesh University (BU). He holds a Bachelor of Science in Electrical and Computer Engineering from Rajshahi University of Engineering & Technology (RUET). He brings an academic background in electrical and computer engineering and is engaged in teaching and academic activities in the field of computer science and engineering.
Academic Experience
Mahmud Naeem has been serving as a Lecturer in the Department of Computer Science and Engineering at Bangladesh University since January 15, 2026. In this role, he is involved in teaching, student guidance, and academic activities within the department.
Professional Practice
Prior to joining Bangladesh University, Mahmud Naeem completed an Industrial Attachment as a Trainee at BJIT, Dhaka, Bangladesh, from March 19 to March 28, 2024. This industrial attachment provided practical exposure to a professional technology environment and complemented his academic background in Electrical and Computer Engineering.
Area of Interest
Python (computer programming), machine learning, Deep learning, Reinforcement Learning, MATLAB, Overleaf LaTex editor.
Research Work
1. 2025 – CURRENT: A Hybrid QdDA-RF Framework with Probabilistic Feature Augmentation for Power Transmission Line Fault Identification and Categorization-
Manuscript accepted for publication (First Author) in Lecture Notes in Networks and Systems published by Springer
and presented at 3rd International Conference on Big Data, IoT and Machine Learning (BIM 2025)
2. 2025 – CURRENT: SHAP-Interpretable QDA-RF Hybrid Model with Probabilistic Feature Augmentation for Transmission Line Fault Detection, Classification, and Performance Analysis Under Cyber Attack Scenarios-
Manuscript currently under preparation for journal submission. This is an extension of the original bachelor thesis that investigates the impact of False Data Injection (FDI) attacks on the performance of the cascaded QDA-RF pipeline.
2025: Enhancing Adult Income Prediction Using PSO-Tuned LightGBM and Explainable AI-
Authors: Shawon Tajwar Jahan; Hafsa Binte Kibria; Mahmud Naeem | Journal Name: 2025 International Conference on Quantum Photonics, Artificial Intelligence, and Networking (QPAIN) | Volume, Issue and Pages: pp. 1-6, doi: 10.1109/ QPAIN66474.2025.11172107. | Publisher: IEEE
