We use machine learning to accurately forecast electricity prices. Our live customers, including Enel, use our software to improve revenue by millions of dollars per year.
My background is in development and deployment of theoretical statistical methods in the context of renewable resource modelling. Prior to founding inBalance, I worked in both the US and Spain building fluid dynamics models of wind farms under the NSF WINDINSPIRE grant. I've implemented my research across a number of fields, ranging from anti-gerrymandering work to baseball scheduling.