Mohammed Ibrahim Husssain
Assistant Professor
Mohammed Ibrahim Husssain is an Assistant Professor & Central Coordinator in the Department of Computer Science and Engineering (CSE) at Bangladesh University (BU). He holds a Bachelor of Science in Computer Science & Engineering from The National Technical University of Ukraine, Kyiv, Ukraine; an MSc in E-Commerce from London School of Business Administration (LSBA), United Kingdom; and a Post Graduate Diploma in Networking from The Computeach Ltd., University House, West Midlands, United Kingdom. He has extensive academic and professional experience in computer science, networking, software development, machine learning, and information technology.
Academic Experience
Mohammed Ibrahim Husssain has been serving as an Assistant Professor & Central Coordinator in the Department of Computer Science and Engineering at Bangladesh University since February 23, 2013. Previously, he served as a Senior Lecturer at Bangladesh University from April 8, 2012 to February 22, 2013, and as a Lecturer from December 5, 2007 to April 7, 2012. He has also served as an Adjunct Faculty (Assistant Professor) at Presidency University and Manarat International University, where he taught Computer Programming Language (CPL), Data Communications and Computer Networks (DCCN).
Professional Practice
His professional experience includes working as a System Administrator and CCNA Trainer at Protocol Infosys from February 2005 to October 2007. Earlier, he served as a Supervisor for Network & Online Stock Control Management at Morrison Plc (formerly Safeway Plc), Surrey, England, from November 2000 to January 2005. He also worked as a Computer Lab and LAN Assistant-Supervisor in the Department of Special Computer Systems and Networks, Faculty of Applied Mathematics, at The National Technical University of Ukraine, Kyiv, from July 1999 to June 2000.
He possesses strong technical expertise in C, C++, C#, Java, and Python, along with computer networking, network design and implementation, machine learning, deep learning, and image processing. He is also experienced in PROLOG, MATLAB, MySQL, SQL Server, HTML, CSS, PHP, Adobe Illustrator, Adobe Photoshop, and Microsoft Office. His professional certifications include Microsoft Certified IT Professional (MCIP), Microsoft Certified Technology Specialist (MCTS), and Cisco Certified Network Associate (CCNA).
Area of Interest
1. Data Science
2. Machine Learning
3. Deep Learning
4. Explainable Artificial Intelligence
5. Feature Engineering
6. Natural Language Processing
RESEARCH PAPER PUBLICATION IN REFEREED JOURNALS:
1. Swarna, R. A., Hussain, M. I., Iqbal, M. S., Mamun, M., & Chowdhury, S. H. (2023) ILF: A Quantum Semi-Supervised Learning Approach for Binary Classification. International Journal of Advanced Research in Computer Science and Communication Engineering, 12(1), 88-96. https://doi.org/10.17148/IJARCCE.2023.121112
2. Chowdhury, S. H., Mamun, M., Shaikat, T. A., Hussain, M. I., Iqbal, S., & Hossain, M. M. (2025). An Ensemble Approach for Artificial Neural Network-Based Liver Disease Identification from Optimal Features through Hybrid Modeling Integrated with Advanced Explainable AI. Medinformatics, 2(2), 107-119. https://doi.org/10.47852/bonviewMEDIN52024744
3. Hussain, M. I., Munir, A., Mamun, M., Chowdhury, S. H., Uddin, N., & Hossain, M. M. (2025). A Transparent House Price Prediction Framework Using Ensemble Learning, Genetic Algorithm- Based Tuning, and ANOVA-Based Feature Analysis. FinTech, 4(3), 33. https://doi.org/10.3390/fintech4030033
4. Chowdhury, S. H., Mamun, M., Hossain, M. M., Hossain, M. I., Iqbal, M. S., & Kashem, M. A. (2024, April). Newborn Weight Prediction And Interpretation Utilizing Explainable Machine Learning. In 2024 3rd International Conference on Advancement in Electrical and Electronic Engineering (ICAEEE) (pp. 1-6). IEEE. https://doi.org/10.1109/ICAEEE62219.2024.10561798
5. Mamun, M., Chowdhury, S. H., Hussain, M. I., & Iqbal, M. S. (2024, October). Early-Stage Diabetes Risk Prediction Utilizing Machine Learning with Explainable AI from Polynomial and Binning Feature Generation. In 2024 2nd International Conference on Information and Communication Technology (ICICT) (pp. 26-30). IEEE. https://doi.org/10.1109/ICICT64387.2024.10839710
6. Chowdhury, S. H., Mamun, M., Hussain, M. I., & Iqbal, M. S. (2024, October). Brain Stroke Prediction using Explainable Machine Learning and Time Series Feature Engineering. In 2024 2nd International Conference on Information and Communication Technology (ICICT) (pp. 16-20). IEEE. https://doi.org/10.1109/ICICT64387.2024.10839683
7. Shaikat, M. T. A., Chowdhury, S. H., Shovon, M., Hossain, M. M., Hussain, M. I., & Mamun, M. (2025, February). Explainability Elevated Obstructive Pulmonary Disease Care: Severity Classification, Quality of Life Prediction, and Treatment Impact Assessment. In 2025 International Conference on Electrical, Computer and Communication Engineering (ECCE) (pp. 1-6). IEEE. https://doi.org/10.1109/ECCE64574.2025.11013299
8. Chowdhury, S. H., Mamun, M., Shaikat, M. T. A., Hussain, M. I., & Hossain, M. M. (2025, February). Improving Network Classification Accuracy through Feature Clustering and Ensemble Machine Learning with Explainable AI. In 2025 International Conference on Electrical, Computer and Communication Engineering (ECCE) (pp. 1-6). IEEE. https://doi.org/10.1109/ECCE64574.2025.11013433
9. Mamun, M., Ali, M. S., Chowdhury, M. S. A., Chowdhury, S. H., Hussain, M. I., & Hossain, M.M. (2025, February). A Differential Privacy and TOPSIS Enhanced Explainable Machine Learning Framework for Diabetes Risk Diagnosis. In 2025 International Conference on Electrical, Computer and Communication Engineering (ECCE) (pp. 1-6). IEEE. https://doi.org/10.1109/ECCE64574.2025.11013439
10. Chowdhury, S. H., Hussain, M. I., Chowdhury, M. S. A., Ali, M. S., Hossain, M. M., & Mamun, M. (2025, June). Hepatitis C Detection from Blood Donor Data Using Hybrid Deep Feature Synthesis and Interpretable Machine Learning. In 2025 2nd International Conference on Next- Generation Computing, IoT and Machine Learning (NCIM) (pp. 1-6). IEEE. https://doi.org/10.1109/NCIM65934.2025.11160156
11. Mamun, M., Hussain, M. I., Ali, M. S., Chowdhury, M. S. A., Hossain, M. M., & Chowdhury, S.H. (2025, June). Interpretable Heart Failure Identification Utilizing Auto Machine Learning Tools. In 2025 2nd International Conference on Next-Generation Computing, IoT and Machine Learning (NCIM) (pp. 1-6). IEEE. https://doi.org/10.1109/NCIM65934.2025.11159854
12. Chowdhury, S. H., Hussain, M. I., Shovon, M., Morzina, M. S., Hossain, M. M., & Mamun, M. (2025, July). LoRA and ReFT Optimized Explainable Machine Learning and Deep Learning Framework for SMS Spam Detection. In 2025 International Conference on Quantum Photonics, Artificial Intelligence, and Networking (QPAIN) (pp. 1-6). IEEE. https://doi.org/10.1109/QPAIN66474.2025.11171842
13. Mamun, M., Hussain, M. I., Ali, M. S., Chowdhury, M. S. A., Chowdhury, S. H., & Hossain, M.M. (2025, July). An Explainable Ensemble Learning Framework with Feature Optimization for Accurate Maternal Health Risk Prediction. In 2025 International Conference on Quantum Photonics, Artificial Intelligence, and Networking (QPAIN) (pp. 1-6). IEEE. https://doi.org/10.1109/QPAIN66474.2025.11172243
14. Das, K., Mamun, M., Safat, Y., Hussain, M. I., Hossain, M. M., & Chowdhury, S. H. (2025, July). Optimized Feature-Driven Dengue Diagnosis Using Explainable Machine Learning Approaches. In 2025 International Conference on Quantum Photonics, Artificial Intelligence, and Networking (QPAIN) (pp. 1-6). IEEE. https://doi.org/10.1109/QPAIN66474.2025.11171726
15. Hussain, M. I., Chowdhury, S. H., Shovon, M., Morzina, M. S., Hossain, M. M., & Mamun, M. (2025, July). SENet-Augmented Explainable Deep Feature Framework with Machine Learning for Breast Tumor Detection in Ultrasound Imaging. In 2025 International Conference on Quantum Photonics, Artificial Intelligence, and Networking (QPAIN) (pp. 1-6). IEEE. https://doi.org/10.1109/QPAIN66474.2025.11171635
16. Mamun, M., Hussain, M. I., Ali, M. S., Chowdhury, M. S. A., Chowdhury, S. H., & Hossain, M.M. (2025, July). Privacy-Preserving Prediction of Chronic Kidney Disease Using Ensemble Machine Learning with Laplacian Differential Privacy and Explainable AI. In Proceedings of the International Conference on Data Science, AI and Applications (ICDSAIA 2025), Communications in Computer and Information Science (CCIS). Springer, Singapore. (Accepted)
17. Hussain, M. I., Parvin, K., Shovon, M., Chowdhury, S. H., Hossain, M. M., & Mamun, M. (2025). Explainable Machine Learning Framework for Accurate Crop Suitability Prediction from Soil Properties. In International Conference on Multidisciplinary Computer Science, Electrical, Business & Literature (ICMCEL). Dhaka, Bangladesh IEEE. (Accepted)
PRESENTATION AT CONFERENCES:
1. 3rd International Conference on Advancement in Electrical and Electronic Engineering (ICAEEE- 2024), DUET, Gazipur, Bangladesh.
2. Newborn Weight Prediction And Interpretation Utilizing Explainable Machine Learning
3. 2nd International Conference on Information and Communication Technology (ICICT-2024), BUET, Dhaka, Bangladesh.
4. Brain Stroke Prediction using Explainable Machine Learning and Time Series Feature
5. Early-Stage Diabetes Risk Prediction Utilizing Machine Learning with Explainable AI from Polynomial and Binning Feature Generation.
6. 4th International Conference on Electrical, Computer and Communication Engineering (ECCE- 2025), CUET, Chittagong, Bangladesh.
7. Improving Network Classification Accuracy through Feature Clustering and Ensemble Machine Learning with Explainable AI..
8. 2nd International Conference on Next-Generation Computing, IoT and Machine Learning (NCIM- 2025), DUET, Gazipur, Bangladesh.
9. Hepatitis C Detection from Blood Donor Data Using Hybrid Deep Feature Synthesis and Interpretable Machine Learning.
10. International Conference on Data Science, AI and Applications (ICDSAIA-2025), EATL Innovation Hub, Gazipur Hitech City, Bangladesh.
11. Privacy-Preserving Prediction of Chronic Kidney Disease Using Ensemble Machine Learning with Laplacian Differential Privacy and Explainable AI.
12. 2025 IEEE International Conference on Quantum Photonics, Artificial Intelligence, and Networking (QPAIN-2025), Rangpur, Bangladesh.
13. LoRA and ReFT Optimized Explainable Machine Learning and Deep Learning Framework for SMS Spam Detection.
14. SENet-Augmented Explainable Deep Feature Framework with Machine Learning for Breast Tumor Detection in Ultrasound Imaging.
RESEARCH PAPERS IN PROGRESS:
1. Mamun, M., Chowdhury, S. H., Akter, S., Biswas, B. R., Hussain, M. I., & Hossain, M. M. (2025). Identification of Maternal Health Risk from Optimal Features Using Explainable Machine Learning. Telematics and Informatics Reports. Elsevier. (Third Revision).
2. Mamun, M., Hossain, M. M., Hussain, M. I., Chowdhury, S. H., Alahmadi, T. J., & Moni, M. A. (2025). Privacy-Preserving Maternal Health Risk Prediction Utilizing Differential Privacy with Explainable Machine Learning. Applied Soft Computing. Elsevier. (Under Review).
3. Hussain, M. I., Chowdhury, S. H., Mamun, M., Hossain, M. M., Parvez, A. H. M. S., & Munir, A. (2025). Multi-Objective Optimized Differential Privacy with Interpretable Machine Learning for Brain Stroke and Heart Disease Diagnosis. SN Computer Science. Springer. (Submitted).
4. Hussain, M. I., Chowdhury, S. H., Mamun, M., Hossain, M. M., Parvez, A. H. M. S., & Munir, A. (2025). Identification of the Source of AI-Generated Text Using Explainable Machine Learning
5. with Manual and Deep Learning Fusion Feature Extraction Techniques. Electronics. MDPI. (Submitted).
6. Hussain, M. I., Chowdhury, S. H., Hossain, M. M., & Mamun, M. (2025). NeuroBlend-3: Hybrid Deep and Machine Learning Framework with Explainable AI for Multi-Class Brain Tumor Detection Using MRI Scans. Medinformatics. Bon View Publishing Pte. Ltd. (First Revision).
7. Hussain, M. I., Chowdhury, S. H., Hossain, M. M., & Mamun, M. (2025). Explainable AI-Driven Tree-Selection Stacking Random Forest with Hybrid Feature Synthesis for Lung Cancer Survival Time Prediction. 2nd International Conference on Computing, Applications, and Systems (COMPAS 2025). Islamic University, Kushtia, Bangladesh: IEEE. (Submitted).
8. Hussain, M. I., Shovon, M., Parvez, A. H. M. S., Mamun, M., & Chowdhury, S. H. (2025). A Comparative Study of CNN and Vision Transformer Methods for Rice Variety Classification with XAI. In 2nd International Conference on Computing, Applications, and Systems (COMPAS 2025). Islamic University, Kushtia, Bangladesh: IEEE. (Submitted).
9. Dipu, A., Chowdhury, S. H., Hussain, M. I., Hossain, M. M., & Mamun, M. (2025). Comparative Evaluation of Machine Learning Models for Non-Invasive Hypoglycemia Detection with XAI Methods. In 2nd International Conference on Computing, Applications, and Systems (COMPAS 2025). Islamic University, Kushtia, Bangladesh: IEEE. (Submitted).
10. Onti, W. H., Chowdhury, S. H., Hussain, M. I., Hossain, M. M., & Mamun, M. (2025). A Deep Learning and Explainable AI Framework to Rank Solar Irradiance Zones in Southern Bangladesh. In 2025 International Conference on Intelligent Data Analysis and Applications (IDAA). Daffodil International University, Dhaka, Bangladesh: IEEE. (Submitted).
