I do math that powers the power system. Specifically, I study questions that demand novel mathematical frameworks, pose serious computational challenges, or warrant an in-depth economic analysis in the application domain of the electric power grid. My research into such questions often leads to the development of tools and techniques that apply more broadly to networked cyber-physical systems with many interacting agents that have strategic incentives. CV, Google Scholar.
I am broadly interested in algorithmic challenges, business modeling, and market design questions, largely motivated by the current transformation of the electric power grid. Some research themes are informed by current events and have broader applications. J=Journal; C=Conference; P=Preprint; B=Book Chapter.
Uncertainty is unavoidable in planning and operations of engineering systems. I work on optimization and pricing decisions that process uncertainty through a suitable risk measure. An example direction is risk-sensitive wholesale electricity market design.
Different decision-makers often operate assets at different nodes of an underlying network, who either collaborate or compete with each other. I study distributed algorithms for coordination of such agents and the analysis/design of market platforms that operate over such a network.
Electrification of ground transport and aviation will make the transportation and the energy infrastructure interdependent. I study rigorous mathematical frameworks to optimize decisions against this interdependency of the two infrastructures.
Nonconvex feasible sets arise naturally in resource allocation over certain physical networks, such as the electric power grid. My interest lies in the analysis and design of market platforms that operate over such networks.
I am interested in data-efficient mechanisms to learn properties of dynamical systems, combining operator-theoretic approaches and change-detection algorithms.
With a combination of theoretical modeling and data, I study resource management questions to contain the impacts of an epidemic spread.