Maryam Baghkarvasef’s research lies at the intersection of artificial intelligence, energy systems, and climate resilience. As a Ph.D. candidate in electrical and computer engineering, her recent work focuses on applying AI and optimization techniques to hydropower modeling and scheduling, an area that is becoming increasingly critical as extreme weather events grow more frequent and severe.
Hydropower is a clean and renewable energy source, yet its operation is inherently dependent on water availability. During prolonged heatwaves, rising temperatures increase evaporation in reservoirs, alter precipitation patterns, and disrupt inflows. At the same time, electricity demand surges as air conditioning use spikes, often driving sharp increases in market prices. Together, these pressures can strain hydropower systems and limit water availability when it is needed most.
To address this challenge, Baghkarvasef has developed advanced machine learning and deep learning models that forecast key variables such as precipitation, evaporation, reservoir inflows, power demand, and market prices. These tools allow hydropower operators to anticipate extreme events, store water more strategically, and better prepare to meet peak electricity demand while maintaining system reliability.
Her work has already moved beyond theory into practice. As an intern at Grid Elevated, a startup affiliated with the University of Utah, she collaborates directly with utility partners in Utah, an effort that enriches her research by grounding it in operational realities. Baghkarvasef has published three papers on this research, two journal articles and one conference paper, in highly reputable venues, and her work has received significant international attention within the energy systems and AI research communities.
Looking ahead, Baghkarvasef’s goal is clear: she wants the AI-driven models she builds to be actively used by hydropower operators and energy utilities to prepare for tomorrow’s challenges, whether driven by climate extremes or evolving energy demands. Her research offers a powerful example of how artificial intelligence can strengthen the resilience of critical infrastructure in a changing world.
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