Mohammed Ibrahim Husssain
Assistant Professor
Academic Qualifications:
1. Bachelor of Science in Computer Science & Engineering, The National Technical University of Ukrain,Kiev, Ukraine.
2. Msc in E-Commerce, London School of Business administration LS(BA).
3. Post Graduate Diploma in Networking, The Computeach Ltd,University House, West Midland, UK..
PROGRAMMING SKILLS:
1. Proficient in C, C++, C#, Java, and Python.
2. Computer Networking, Network design & Implementation
3. Extensive hands-on experience in machine learning, deep learning, and image processing.
4. Strong understanding of PROLOG.
5. Basic proficiency in MATLAB.
6. Skilled in database languages such as MySQL and SQL Server.
7. Fundamental knowledge of HTML, CSS, and PHP.
8. Professionally skilled on Adobe Illustrator.
9. Basic skills in Adobe Photoshop.
10. Professionally skilled on MS Office.
CERTIFICATIONS:
1. Microsoft Certified IT Professional (MCIP)
2. Microsoft Certified Technology Specialist (MCTS)
3. Cisco Certificate Network Associates(CCNA)
Professional Experience:
1. Assistant Professor & Central Coordinator, Department of Computer Science & Engineering, Bangladesh University. From 23th February, 2013 – to til date.
2. Senior Lecturer, Department of Computer Science & Engineering, Bangladesh University. From 8th April, 2012 to 22tj February, 2013
3. Lecturer, Department of Computer Science & Engineering, Bangladesh University. From 5th December, 2007 to 7th April, 2012
4. Adjunct Faculty (Assistant Professor), Presidency University. Subject: Computer Programming Language(CPL), Data Comunications and Computer Networks(DCCN)
5. Adjunct Faculty (Assistant Professor), Manarat International University, Subject: Computer Programming Language(CPL), Data Comunications and Computer Networks(DCCN)
6. System Administrator (CCNA Trainer), Protocol Infosys. From Feb,2005 to October 2007.
7. Supervisor (Network & Online Stock Control Management), Morrison Plc (former Safeway Plc), Surrey, ENGLAND, UK., from November, 2000 to January, 2005
8. Computer Lab and LAN Assistant-Supervisor, Faculty of Applied Mathematics De artment of "Special Computer Systems and Networks" under The National Technical University of Ukraine, KIEV, UKRAINE. From July 1999 To June 2000
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).