At Lyft, I work on buidling tools for scientists, including simulation. I've also worked on many interesting optimization, forecasting, and machine learning problems. The 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.
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