Dynamic pricing and demand response will be important features of smart grids and future energy networks. Understanding how electricity consumers or electric vehicles respond to price signals is extremely important. The goal of this project is to develop low-complexity dynamical system models for the aggregate response of a large number of agents (e.g., electricity consumers) to a common signal (e.g., price). In response to an input signal, the individual agents implement a decision (an optimal control law) to minimize their own cost over a selected time horizon. This individual agent model mapping the common signal to the optimal decision is assumed known. It is desirable to develop reduced order dynamic models for describing the overall system that maps the input (e.g., price) to the aggregate output (e.g. aggregate consumption).

I have worked with Professor David Autor (Economics} on the effects of rent control deregulation on property prices and neighborhood income in Cambridge, and on modeling coal plant electricity production at DE Shaw. I helped start the Indian Mobile Initiative, a six week boot camp on entrepreneurship and Android Programming in India.