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"A Multivariate Bayesian Approach to Modeling Vulnerability Discovery in the Software Security Lifecycle," Ph.D. dissertation, The George Washington University, 2018

Dissertation presentation is available here and here
"Bayesian-Model Averaging Using MCMCBayes for Web-Browser Vulnerability Discovery," Reliability Engineering & System Safety, Volume 183, 2019, Pages 341-359

"Multivariate Models Using MCMCBayes for Web-Browser Vulnerability Discovery," Reliability Engineering & System Safety, Volume 176, 2018, Pages 52-61

MCMCBayes framework: MCMCBAYES is a readily extensible, open-source, object-oriented software library supporting Markov chain Monte Carlo (MCMC) based Bayesian analyses using MATLAB. It was initially written to assist in the evaluation of several popular fault counting models applied to modeling software vulnerability discovery counts (Vulnerability Discovery Models, or VDMs).

"Predicting Post-Release Software Security Fault Discovery Using Expert Judgment Elicitation and Bayesian Computed Effort-Dependent Models," International Doctoral Symposium on Empirical Software Engineering, October 9th, 2013, Baltimore, MD, USA