At Lyft, I work on buidling tools for data science, including simulation. I've also worked on many interesting optimization, forecasting, and machine learning problems. The data science team is hiring in SF and Seattle - get in touch if you are interested:
adam.greenhall [at] lyft.com
For my PhD research I wrote software to schedule electrical power systems with uncertain wind energy. I focused on improving algorithms to create wind power scenarios from forecasts and historical data. I evaluated these algorithms based on stochastic unit commitment simulations of the Texas power system. Each simulation was a series of large stochastic optimization problems, which I ran on the UW's high-performance computer cluster. Along the way I created a Python package for power systems optimization called Minpower.