Yifan Zhou
Yifan Zhou is reshaping the future of energy systems through a blend of quantum computing, artificial intelligence and power systems engineering.
A 2025 finalist for the Discovery Prize, Zhou, an assistant professor in the Department of Electrical and Computer Engineering, is gaining recognition for her pioneering approach to one of the energy sector’s most pressing challenges: how to ensure stable, reliable and intelligent power grid operations in an increasingly complex and data-heavy world.
“Our approach is about rethinking power grid operations through cutting-edge quantum and AI technologies, ultimately paving the way for a more reliable energy sector,” said Zhou. Her research explores how emerging computational methods can address the unprecedented demands placed on today’s power grids to create systems that are more reliable and more affordable than ever before.
Zhou’s interest in power systems began early, in her undergraduate studies at Tsinghua University, where she graduated with the highest distinction in 2014. After earning her PhD in 2019 at Tsinghua, she joined Stony Brook as a postdoctoral researcher and later became a faculty member in 2022. Her research sits at the intersection of power engineering and advanced computational science, where the lines between physical infrastructure and digital intelligence are increasingly blurred.
In the past, power grid operations relied on centralized energy generation and relatively straightforward distribution models. Today, Zhou notes, the situation is dramatically more complicated. “We have a lot of new generation sources like distributed energy in communities, and massive demands not only from homes and industries but also from technologies like AI and data centers,” she explained. “This introduces enormous computational challenges — managing these systems reliably in real time across countless possible scenarios.”
Zhou’s work focuses on solving these problems through quantum computing, particularly in how it can outperform classical methods in simulating and operating ultrascale power systems. “Classical computing has its boundaries,” she said. “Even supercomputers can face inherent limitations. In contrast, quantum computing has the potential to dramatically reduce computational complexity and increase efficiency, especially for problems with high complexity, which is exactly the case in power systems.”
A prime example Zhou’s team has focused on is the electromagnetic transient (EMT) simulation for power systems. This type of calculation is essential to integrating new generations and managing unexpected events on the grid, but it’s also computationally demanding.
“EMT simulation is a typical computational bottleneck the industry faces,” Zhou explained. “We’ve developed quantum-enhanced algorithms that show potential to overcome these limitations. That’s why utilities have taken an interest in our work.” Zhou is now collaborating with ISO New England to prototype her methods for real-world power systems.
“The main difference in our approach is that we are performing the computation entirely in quantum space,” Zhou said. “This allows us to use quantum operators that make certain calculations — very complex in classical terms — much simpler and more efficient.”
In addition to her quantum work, Zhou is also exploring the integration of AI into power system analysis. Her goal is to develop intelligent, adaptive systems capable of handling real-time data from massive sensors and adjusting operations instantaneously to prevent outages. “The goal is reliability,” she said. “We want the power grid to operate without interruption, even when unexpected events occur. That’s where quantum and AI together can be powerful.”
“Reliable power means that the system continues to operate smoothly under all kinds of conditions — avoiding blackouts, fluctuations, or failures that could affect homes, hospitals, or industry,” she said. Quantum computing, she believes, can contribute to this goal by enabling ultra-effective decision-making that anticipates and mitigates potential disruptions before they escalate.
Beyond her research contributions, Zhou is also committed to mentoring the next generation of scientists, especially young women entering STEM fields. Last summer, she supervised two high school students on a project combining quantum computing and AI in power systems. Despite having little background in quantum computing, the students quickly learned the concepts, conducted experiments and co-authored a paper that received the AI Youth Star Award at the 2024 IEEE International Conference on Big Data.
“This experience really inspired me,” Zhou said. “I always tell young researchers: don’t be afraid to try. With the resources available today — from generative AI tools to open-source code — anyone with curiosity and a computer can explore cutting-edge technologies. Just start. Don’t wait to be an expert.”
Looking ahead, Zhou and her team, in partnership with utilities and industry leaders, will continue to build momentum around applying quantum tools to practical challenges in the energy sector to support smarter, more secure and more reliable infrastructure.