08/06/2026
🎉DOCTORAL DEFENSE ANNOUNCEMENT🎉
Grid operators keeping the lights on during extreme weather, utilities deciding where to invest in solar and wind, manufacturers planning production months ahead — they all face the same challenge: making critical decisions today without knowing exactly what tomorrow holds.
Azadeh’s research develops new data-driven optimization methods to help decision-makers act reliably, efficiently, and equitably under uncertainty. Using chance-constrained, distributionally robust, and sample-based approaches, her work tackles real challenges in production planning, renewable energy, and power system operations — with computationally efficient methods that make advanced optimization practical at scale.
Her findings show that uncertainty can be built directly into decision-making without sacrificing efficiency, offering tools that improve reliability, cut costs, and support more resilient, sustainable, and equitable energy and manufacturing systems.
