My professional expertise lies in the contested terrain between applied mathematics and engineering.I earned a PhD for working towards methods that can very efficiently learn the patterns by which errors emerge in a class of simulations. The goal of the thesis was to balance the impacts of multiple tunable precision parameters in order to get as accurate of a simulation as possible with a fixed computational cost. This, of course, must be done without having explicit knowledge of the simulation's error behavior before it is run, and my work used a rigorous encoding of "intuition" to make it possible.Since then, I have been working on simulation methods for the renewable energy sector. This work has involved a handful of projects with a central theme of getting more information about the performance of wind energy systems from a given unit of computational or engineering effort.