Research Profile
Prospective PhD researcher with a Software Engineering degree and research experience in machine learning, explainable AI, healthcare informatics, and mathematical optimization, alongside a growing interest in agentic AI. My FRGS-funded master’s research focuses on mathematical model development and optimization, while my earlier work addressed dementia and mental-state prediction and medical-image analysis. I have co-authored five journal articles (four published in Q1/Q2) and three conference papers, including a first-author IEEE EEEIC-2025 paper, with more than 88 citations and collaborations spanning Bangladesh, the USA, the UK, and Malaysia. Through doctoral study, I aim to develop reliable, interpretable, and agentic AI systems for healthcare and other high-impact decision-making applications.
Research Interests
Machine Learning · Explainable AI · Agentic AI · Healthcare Informatics · Mathematical Optimization · Artificial Intelligence
Education
- Research Focus: Mathematical Modeling, Optimization, Agentic AI
- Funding: Fundamental Research Grant Scheme (FRGS)
- Supervisor: Dr. Tan Wooi Nee
- CGPA: 3.76 / 4.00 | Faculty: Science and Technology
Research Experience
- Conducted FRGS-funded master’s research by developing a two-stage load-scheduling optimization model, formulating operational constraints, and evaluating demand- and supply-side trade-offs.
- Prepared a first-author IEEE conference paper through model development, validation, and technical writing under the supervision of Assistant Professor Dr. Tan Wooi Nee.
- Built and evaluated prediction workflows using feature selection, ensemble learning, and explainable AI for dementia, mental health, and student performance.
- Contributed to CNN-based medical-image classification, data analysis, and peer-reviewed manuscript preparation under the supervision of Prof. Dr. Md. Asraf Ali.
- Analyzed foreign-exchange data from Islami Bank Bangladesh PLC and summarized findings for research reporting.
Selected Publications
Loading publications...
Key Projects
Dementia Prediction with XAI
Developed a novel integrated logistic regression model enhanced with Recursive Feature Elimination (RFE) and Explainable AI for early dementia detection.
HyOPTEnsemble (Mental Health)
Built a custom-weighted soft-voting hyperparameter optimization ensemble model to predict mental states among university students with high accuracy.
CNN Medical Image Classifier
Designed and trained customized Convolutional Neural Networks (CNN) for classifying Chest X-rays into COVID-19, Pneumonia, and Normal categories.
Technical Skills
AI & Research
Machine Learning, Ensemble Learning, Explainable AI, Agentic AI
Quantitative Methods
Experimental Design, Mathematical Modeling, Optimization, Model Evaluation
Programming
Python, C/C++, Bash, Rust
Databases
Oracle, PostgreSQL, MySQL, NoSQL
Tools & Workflow
Git/GitHub, Docker, Anaconda, LaTeX