Department of Biomedical Engineering (BME)

 

Contact Information:

3^rd Floor, Tower-4, MIST.

Mirpur Cantonment, Dhaka-1216, Bangladesh.

Email: tahmid.zaman@bme.mist.ac.bd

Academic Qualification:

Bachelor of Science in Industrial and Production Engineering
April 2021 – June 2025
Military Institute of Science and Technology

Undergraduate Thesis: AI-Based Hybrid Framework for Solar PV Fault Detection & Prediction of Solar Power Generation
Supervisor: Maj. Mohammad Naim Uddin, Program Coordinator, IPE

Research Interests:

Machine Learning, Computer Vision, Hyperspectral Imaging, Remote Sensing, Data-Driven Modeling, Internet of Things (IoT)

Professional Experience:

1. Research Assistant
January 2026 – Present
Department of Biomedical Engineering
Military Institute of Science and Technology, Mirpur DOHS, Dhaka, Bangladesh

2. Business Analyst Intern
October 2025 – December 2025
WMarketing Digital Agency, Mirpur DOHS, Dhaka, Bangladesh

3. Business Analyst Intern
February 2024 – June 2024
Kodeline, Montreal, Canada

4. Industrial Attatchment
January 2024 – February 2024
Unilever, Kalurghat, Chittagong, Bangladesh

Achievements:

1. 60% Scholarship,Internation professional qualification, International Supply Chain Education Alliance (ISCEA)

2. 1st Runner-Up, Full Stack Web Development Competition, MIST Innovation Club.

Extracurriculur Activities:

1. Vice President – App and Web Development Department

MIST Innovation Club (MIC), MIST

2. Team Leader - App and Web Development Department

OptiMIST, MIST

Research Works:

1. Human-Machine Collaborative Approach for Accurate Diabetic Foot Ulcer Segmentation

Cognitive Computation, Under Review - Jul, 2025

• Developed CFUD-3010, a large-scale DFU segmentation dataset by combining existing datasets and employing a human-machine collaborative annotation strategy to generate ground-truth masks.

2. Human-Machine Framework for Unmanned Aerial Vehicle Image Segmentation for Post-disaster Damage Assessment

Engineering Applications of Artificial Intelligence, Under Review - August, 2025

• A semantic segmentation framework that classifies buildings according to structural damage severity from unmanned aerial vehicle imagery.
• Used Segmentation Models (UNet, ResUNet) combined with imagenet pretained encoders (ResNet101) to classify and segment damaged areas.

3. Multi-Encoder Transformer Fusion Network for RGB-Thermal Segmentation of Rooftop Thermal Bridges

Expert System with Applications, Under Review - December, 2025

• Performed spectral analysis on grapevine leaf, and targeted band selection on 204-channel HSI data, enabling a 85.3% dimensionality reduction.
• Developed a cross-modal hyperspectral classification framework with lightweight 3D-CNN spectral–spatial encoding, to achieve state-of-the-art grapevine leaf disese discrimination.

4. Explainable Machine Learning for Glioma Classification Using Gene Expression Analysis

Journal of Neuro-Oncology, Under Review - January, 2026

• Conducted gene pair analysis to identify prognostic biomarkers and molecular signatures associated with glioma progression and patient survival.

5. Hybrid GWO-XGBoost Framework for Blast Induced Ground Vibration Prediction: Integration of Genetic Algorithm Optimized Scaled Distance

ICMERE CUET, January 2026

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6. Associations between Climate Change and Infectious Diseases: A Systematic Review

International Journal of Medical Informatics, Under Review - January, 2026

• Performed a PRISMA-compliant systematic review, examining how climate variables affect vector-borne, water-borne, food-borne, and zoonotic disease dynamics.

7. A Detection-Guided Self-ONN Enhanced EfficientNet-UNet Framework for Automated Stroke Lesion Segmentation

• Enhanced lesion segmentation through detection-guided ROI cropping and Self-ONN architectures, achieving improved boundary delineation for small and fragmented lesions.