Md. Mesbahuddin Hasib
Lecturer
Academic Qualification:
1. Bachelor of Computer Science & Engineering, Rajshahi University of Engineering and Technology (RUET), Rajshahi.
2. Higher Secondary School Certificate (HSC), Dhaka Residential Model College, Dhaka.
3. Secondary School Certificate (SSC), Dhaka Residential Model College, Dhaka.
Professional Experience:
1. Lecturer, Department of CSE, Bangladesh University, from 01, January, 2026 to Present.
Area of Interest
Machine Learning in Healthcare, Deep Learning for Biomedical Signal Processing, Sleep Stage Classification, Medical Image Analysis, Time-Series Modeling, EEG Signal Interpretation.
Research Work
RESEARCH:
1. Improved Skin Lesion Detection with Double Layer Concatenated DenseNet Using Transfer Learning and Attention Modules- (Sep. 2023 – Apr. 2024)
Undergraduate Research – Supervisor: Md. Farukuzzaman Faruk, Assistant Professor, Dept. of CSE, RUET Published at 2024 IEEE PEEIACON — DOI: 10.1109/PEEIACON63629.2024.10800726
a. Developed a DenseNet-based deep learning architecture enhanced with stacked attention modules to classify skin lesions from dermoscopic images.
b. Introduced the Double Layer Concatenated DenseNet (DLCD) model, achieving 91.61% accuracy on the ISIC 2019 dataset.
c. Applied Grad-CAM to visualize critical lesion areas, improving model interpretability.
d. Published and indexed in IEEE Xplore, ResearchGate, and Google Scholar.
2. A Multi-Stage Neural Pipeline: Integrating 1D Convolutional, Recurrent, and Invertible Layers for Advanced Time-Series Modeling- (Nov. 2024 – Present), Undergraduate Thesis – Supervisor: Md. Farukuzzaman Faruk, Assistant Professor, Dept. of CSE, RUET
a. Designing an end-to-end deep learning pipeline combining 1D CNN, BiLSTM, and Invertible Neural Networks (INNs) for efficient sleep stage classification.
b. Focused on lightweight architecture and interpretability to facilitate early detection of sleep disorders using EEG signals from the Sleep-EDF dataset.
c. Aiming to build a clinically usable system to support sleep research and improve patient care through automated stage identification.
PROJECTS:
1. Computer Architecture using Verilog- Under Supervision of Nahin Ul Sadad, Assistant Professor, Dept. of CSE, RUET. github.com/Mesbah5411/Computer-Architecture-using-Verilog
a. Implemented core components of computer architecture including ALU, control units, and register file using Verilog HDL.
b. Simulated and verified modules using Icarus Verilog and GTKWave; tested logical correctness through custom test- benches.
c. Gained hands-on experience with hardware description languages and low-level architectural design.
2. Hospital Management System-
Under Supervision of Bayezid Islam, Assistant Professor, Dept. of CSE, RUET
github.com/Mesbah5411/Hospital Management System
a. Developed a desktop-based hospital management system using Java with Object-Oriented Programming (OOP) princi- ples.
b. Integrated MySQL database to handle patient data, appointments, medical history, and billing records.
c. Implemented GUI-based user interface for smooth navigation and operation by hospital staff.
d. Ensured efficient backend logic with secure CRUD operations and modular code design for maintainability.
3. OpenGL 3D Interactive Scene-
Under Supervision of Md. Sozib Hossain, Lecturer, Dept. of CSE, RUET
github.com/Mesbah5411/OpenGL3D-project
a. Developed a fully interactive 3D scene using OpenGL and GLUT with object transformations, camera controls, and keyboard navigation.
b. Enabled real-time selection and manipulation of cube, pyramid, and sphere using keyboard-controlled translation, rota- tion, and scaling.
c. Introduced auto-rotation for selected objects and created a smooth and user-friendly graphical interface.
4. Attendance Sheet Management System-
Under Supervision of Barshon Sen, Assistant Professor, Dept. of CSE, RUET
github.com/Mesbah5411/Attendance-Project
a. Built a web-based attendance management platform using PHP, MySQL, HTML, and CSS to simplify record keeping.
b. Added functionality for adding new users, marking attendance, and viewing daily summaries in a responsive layout.
c. Ensured data consistency and basic form validation for improved reliability.
1. Md Mesbahuddin Hasib, Md. Farukuzzaman Faruk Et al. Improved Skin Lesion Detection with Double Layer Concatenated DenseNet Using Transfer Learning and Attention Modules 2024 IEEE International Conference on Power, Electrical, Electronics and Industrial Applications (PEEIA- CON) September 2024 DOI: 10.1109/PEEIACON63629.2024.10800726 Indexed in ResearchGate and Google Scholar
2. Mst.Raisa Rubayet Karim, Md. Farukuzzaman Faruk, Md. Mesbahuddin Hasib Et al. HybEEGNet: An Attention-Enhanced CNN-BiLSTM Model for EEG-Based Motor Movement Classification 2025 28th International Conference on Computer and Information Technology (ICCIT) 19-21 December 2025, Cox’s Bazar, Bangladesh.