Peer-Reviewed Journal Articles
Hewage, S., Sang, Y. (2024). Jackknife empirical likelihood confidence intervals for the categorical Gini correlation. Journal of Statistical Planning and Inference.
URL: https://doi.org/10.1016/j.jspi.2023.106123
Hewage, S. (2025). A Nonparametric K-sample Test for Variability Based on Gini’s Mean Difference. Journal of Statistical Theory and Applications.
URL: https://doi.org/10.1007/s44199-025-00112-3
Aich, A., Murshed, M. M., Hewage, S., Mayeaux, A. (2026). A Copula Based Supervised Filter for Feature Selection in Diabetes Risk Prediction Using Machine Learning. Scientific Reports.
URL: https://doi.org/10.1038/s41598-026-41874-9
Hewage, S., Sang, Y. (2026). Comparing Two Categorical Gini Correlations with Applications to Classification Problems. Statistical Papers.
URL: https://doi.org/10.1007/s00362-026-01865-4
Hewage, I. M., Hewage, S., Schwartz, E. J. (2026). Mathematical Modeling Shows that Overall Infection Burden is Reduced more by Vaccines that Decrease Spread or Accelerate Recovery than those that Lower Severe Infections or Death. Bulletin of Mathematical Biology.
URL: https://doi.org/10.1007/s11538-026-01690-8
Aich, A., Hewage, S., Murshed, M. M. (2026). Copula Based Fusion of Clinical and Genomic Machine Learning Risk Scores for Breast Cancer Risk Stratification. Scientific Reports.
Working Papers
Aich, A., Murshed, M. M., Hewage, S., Mayeaux, A. (2025). CopulaSMOTE: A Copula-Based Oversampling Approach for Imbalanced Classification in Diabetes Prediction. Submitted to BMC Bioinformatics.
URL: https://arxiv.org/abs/2506.17326
Aich, A., Murshed, M. M., Hewage, S., Aich, A. B. (2026). Bayesian Inference for Joint Tail Risk in Paired Biomarkers via Archimedean Copulas with Restricted Jeffreys Priors. Submitted to Statistics in Medicine.
URL: https://arxiv.org/abs/2602.15319
Aich, A., Hewage, S., Murshed, M. M., Aich, A. B., Bandyopadhyay, D. (2026). Dynamic Copula Neural Transition Models for Irregular Bivariate Longitudinal Data.