Passionate about Statistics, Data Science, Machine Learning, and Artificial Intelligence. I enjoy developing data-driven solutions, building predictive models, and conducting research that supports evidence-based decision making.
Publications
Projects
Years of Experience
PLoS ONE • 2025
Developed machine learning models and association rule mining techniques to predict cardiovascular risk factors in the Bangladeshi population.
PLoS ONE • 2025
Developed explainable machine learning models to predict childhood malnutrition in resource-limited settings.
ISASDS 2025, University of Dhaka
Explored diagnostic and prognostic biomarkers for LUAD through integrated bioinformatics workflows and Stacked Machine Learning modeling.
Developed predictive models using Random Forest and XGBoost on national health survey data to assess cardiovascular risk factors.
Integrated RNA-seq data analysis (DESeq2) with ensemble machine learning to identify and validate diagnostic biomarkers.
Applied explainable machine learning (SHAP) on demographic data to predict and interpret undernutrition risk factors in Bangladesh.