With more than 15 years of professional experience, this Ph.D. statistician specializes in statistical inference, estimation, and nonparametric regression, with particular emphasis on uncertainty quantification and the analysis of computationally intensive systems. His work spans cyber security analytics, high performance computing reliability, distributed computing environments, and carbon capture modeling. He has developed and applied statistical frameworks for experimental design, model calibration, sensitivity analysis, and large-scale data analysis. His contributions include the modeling and reliability assessment of complex hardware and software systems and authorship of peer-reviewed publications in applied statistics, reliability engineering, and computational modeling.

His professional experience has involved anomaly detection, stochastic modeling, and predictive modeling and calibration of complex computer systems. In written correspondence addressing construction defect sampling, he clarified that estimating unknown totals from sampled observations should be characterized as statistical inference or estimation rather than extrapolation, underscoring the importance of precise statistical terminology and defensible analytical methodology.