At Applied Research Associates (ARA), I developed Python decision-support software for the Town of Greenwich, combining deterioration forecasts, treatment policies, unit costs, and funding rules to simulate five-year maintenance plans. The recommendations supported capital planning and avoided approximately $20K in additional Cartegraph licensing.
For MDOT SHA, I led technical sensitivity analyses and local calibration of Maryland Pavement ME models, using Oracle SQL to prepare historical pavement data and field observations to evaluate model performance. I also analyzed roadway-friction measurements to inform equipment-reliability decisions.
My work for FHWA/LTPP and FAA included Python Monte Carlo simulations for weigh-in-motion data and automated analysis of airport pavement sensor measurements. I’m pursuing an M.S. in Applied Data Science at UMBC, where my projects have included Spark ML workflows and airport operations data analysis.
