Published peer-reviewed research analyzing AI-driven automation across industries, evaluating efficiency trade-offs, workforce impact, and governance risks using structured industry datasets.

Built supervised machine learning models and conducted structured validation using confusion matrices and cross-validation techniques. Performed data preprocessing (handling missing values, feature engineering, encoding) to improve model accuracy and robustness. Analysed model performance gaps and identified root causes of misclassification to improve reliability.