My research lies at the intersection of mathematical optimization, machine learning, power engineering and economics. The overarching goal of his work is to develop principled and trustworthy decision-making frameworks that improve how critical infrastructure is understood, planned and operated to ensure efficient and reliable performance. His research advances the theoretical and algorithmic foundations of data-driven and optimization-based decision making, with emphasis on scalability, interpretability and robustness. Applications include power and energy systems, safety-critical systems and electricity markets.
ECEN 2410 - Renewable Sources and Efficient Electrical Energy Systems
Primary Instructor
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Spring 2026
Introduces electrical power generation and renewable energy, including solar, wind, micro, hydro, coal, nuclear and natural gas and some of the issues in integrating renewable energy sources in the grid.
