I am a researcher in energy systems, electrical engineering, and applied mathematics, working at the interface of optimization, network-science, and data-driven decision making under uncertainty. My recent work spans stochastic unit commitment, network-constrained optimization, and unsupervised algorithms for uncovering structures in complex data.

A central theme of my recent research at the GRACE lab is how to design and operate low-carbon grids under uncertainty: integrating renewables, storage, flexible demand, and emerging resources (such as floating PV) while maintaining reliability and economic efficiency. Methodologically, I combine optimization, probabilistic modeling, and graph-based algorithms with open-source software.

Most of my work is released as open-source tools and reproducible case studies, and is disseminated through peer-reviewed publications and collaborative projects with system operators, utilities, and industry partners.