B.A., Mount Holyoke College, 1996; Sc.D. Harvard University, 2002; Postdoc, Harvard University
HIV clinical trials, high dimensional data, metabolomics, systems biology, biological networks
My research in biostatistics is strongly motivated by collaborative work in the areas of HIV, cardiovascular disease, diabetes and cancer and is firmly rooted in addressing analytical challenges with applications in public health. In particular, my research involves development and application of statistical methods for:
- Designing and analyzing outcomes related to HIV-related clinical studies
- High-dimensional data settings (p >> n), as seen in genetic, proteomic and metabolomic studies
- Time-to-event outcomes subject to misclassification, as encountered in large-scale epidemiological studies such as the Women’s Health Initiative
- Guo, Y., Balasubramanian, R. (2012). Comparative evaluation of classifiers in the presence of statistical interaction between features in high-dimensionality data settings, International Journal of Biostatistics, 8(1), Article 17.
- Balasubramanian R, Lagakos SW (2010); Estimating HIV incidence based on combined prevalence testing, Biometrics, Vol. 66 (1), pp. 1-10. [PMID: 19397583]
- Guo, Y., Graber, A., McBurney, R.N., Balasubramanian, R. (2010); Sample size and statistical power considerations in high-dimensionality data settings: A comparative study of classification algorithms, BMC Bioinformatics, Vol. 11 (1), pp.447.
- Balasubramanian R, LaFramboise T, Scholtens D, Gentleman R (2004); A graph theoretic approach to testing associations between disparate sources of functional genomics data, Bioinformatics, Vol. 20 (18), pp. 3353-3362
- Balasubramanian R, Lagakos SW (2003); Estimation of time-to-event in the presence of error prone diagnostic tests, Biometrika, Vol. 90, pp. 171-182