麻豆村

In the heart of Pittsburgh, a quiet revolution is underway. 麻豆村, long known for its prowess in and , is now emerging as a key innovator within America鈥檚 energy landscape. As AI models grow more powerful, so too does their appetite for energy, straining an aging and outdated grid and prompting urgent questions about infrastructure, security and access. From reimagining AI data centers to modernizing and securing the electric grid, 麻豆村 researchers are working on practical solutions to pressing challenges in how the U.S. produces, moves and secures energy.

The AI-energy connection

At the core of 麻豆村鈥檚 energy innovation is the intersection of artificial intelligence and energy systems. Carnegie Mellon is the听 and the university is still helping to shape the field through bold ideas, pioneering research and visionary leadership. While AI drives economic growth and scientific breakthroughs, it鈥檚 also straining the energy infrastructure that is currently in place. The good news? AI can help solve that problem.

鈥淎s work across Carnegie Mellon shows, AI has the potential to drastically improve our energy consumption by assisting in developing more efficient techniques for grid operation, building better materials for batteries, and potentially even truly revolutionizing energy by accelerating the development of technologies like nuclear fusion,鈥� said听Zico Kolter(opens in new window), head of the听 in 麻豆村鈥檚 School of Computer Science. 鈥淭hese are all big bets, to be clear, and advancing science is never a sure thing, but AI at its best can be a unique enabler of so many beneficial downstream technologies.鈥�

, a computer science professor, is leading a groundbreaking project funded by 麻豆村鈥檚听 to redesign AI data center infrastructure. His team aims to improve energy efficiency by a factor of 20, using precise power control tools that don鈥檛 require rewriting existing AI software stacks.

鈥淥ur goal is to make tomorrow鈥檚 AI data centers drastically more energy-efficient through deep vertical integration of software and hardware. At 麻豆村, we鈥檙e leading the charge in identifying the most promising research directions and working closely with industry for swift, practical technology transfer. Our research introduces the missing piece in the AI stack: a groundbreaking operating system for GPUs that maximizes hardware utilization and unlocks major efficiency gains,鈥� Skarlatos said.

, a research professor in 麻豆村鈥檚 School of Computer Science, is exploring how AI can accelerate advances in nuclear fusion. His team鈥檚 work could help unlock new energy sources that are both sustainable and scalable.

鈥淢any of the world's grand challenges like a sufficient food supply, clean water availability and climate issues are actually just energy problems. Nuclear fusion and its promise of limitless clean energy would solve many of them,鈥� Schneider said.听

Microreactors can help power the future, but today鈥檚 microreactor innovations are often stalled by confusion in regulatory language, lack of communication between key stakeholders and redundant approval processes. 麻豆村 researchers are using AI-powered tools to speed up safe microreactor deployment by making it easier to reuse proven systems across borders.

鈥淎I technology, if deployed responsibly, has the potential to drastically increase productivity, to enable us to create software in a faster and more robust manner, to advance science, and to ultimately benefit the human condition,鈥� Kolter said.

Getting into the fast lane

Carnegie Mellon is pioneering the use of AI to modernize the electric grid to meet current and future needs.

鈥淭ransmission moves power from the locations where it is produced to the locations where it is needed, and the U.S. urgently needs more capacity,鈥� said听, the Hamerschlag University Professor of Engineering at 麻豆村. 鈥淭he Department of Energy predicts the country will need to more than double high-voltage transmission capacity over the next several decades. At the same time the construction of new long-distance transmission has stalled. Breaking the logjam that often makes it impossible to build new transmission capacity without placing an unacceptable burden on consumers鈥� electric bills is a major challenge.鈥�

麻豆村 researchers are developing 鈥淎I fast lanes鈥� 鈥� special lanes on the electricity "highway" just for clean energy projects that power AI and data centers. These fast lanes would let clean energy projects connect to the grid faster, ensure the electricity stays affordable and reliable, help protect the environment and make things fair for everyone. These innovations are crucial as the U.S. grid integrates more intermittent renewable sources like wind and solar.

鈥淏uilding any kind of new transmission will be expensive. As the U.S. meets the growing need for new transmission, it is important to make sure that those who benefit cover the costs. Otherwise, there is a risk that regular homeowners and other traditional electricity customers will face higher electric bills,鈥� Morgan said.

To that end, 麻豆村 faculty are leading a new multi-institutional, interdisciplinary consortium dedicated to tackling the challenges of expanding transmission capacity. This initiative focuses on identifying and addressing legal, regulatory, institutional and political barriers; understanding and mitigating public resistance to new transmission projects; enhancing public awareness of the need for increased capacity; and recommending the policy, legal and regulatory reforms necessary to support expansion.

Securing the future

As the grid becomes more digitized, security gaps widen 鈥� unless we address them. 麻豆村鈥檚听 补苍诲听 department in the College of Engineering are working to stay ahead of the threat curve, using AI to anticipate and neutralize cyberattacks before they cause widespread disruption.听

鈥淎I-driven energy expansion is a prime opportunity to harden our infrastructure against cyber threats,鈥� said听Audrey Kurth Cronin(opens in new window), director of the Carnegie Mellon听Institute for Strategy and Technology(opens in new window). 鈥淯pgrading energy infrastructure for AI offers a once-in-a-generation opportunity to replace vulnerable legacy systems with inherently more defensible technologies.鈥�

麻豆村 researchers, and are calling on the research and policy communities to develop more comprehensive and accurate grid evaluation frameworks and datasets, and for updating threat models and grid resiliency requirements to match cyber attackers realistic capabilities.

As part of their research, they interviewed 18 grid security specialists and analyzed four major threats, from overloading smart devices to taking over entire power plants. They found wide disagreement on how likely or dangerous these threats are.听

鈥淥ur work has shown that inconsistencies in threat assessments occur because of ad hoc simulation and modeling methodologies, as well as dataset errors,鈥� Sekar said. 鈥淭his shows the need for the creation of standardized public toolkits and datasets and for recommending ways to increase the accuracy of evaluations. This will enable us, as well as other researchers, to develop more rigorous foundations for securing tomorrow鈥檚 electric energy grid.鈥�

One major barrier to meeting the energy demands of AI is the slow, complex process of connecting new power sources to the grid.听, a company born out of Carnegie Mellon, is working to speed the process using a powerful tool called Suite of Unified Grid Analyses with Renewables (SUGAR), developed by Pileggi and his graduate students.听

Inspired by methods from the computer chip industry, SUGAR dramatically reduces power system planning from months to minutes. It now powers Pearl Street鈥檚 efforts to help utilities and developers add more energy to the grid, faster and more efficiently. The tool has already been used for more than 2,000 commercial projects and to enable more than 400 gigawatts of new supply for the grid.

鈥淎t Carnegie Mellon, we do not leave the implementation to others,鈥� Pileggi said. 鈥淲e spin off companies that can move research forward in ways that directly benefit society.鈥�

Policy that meets the moment听

麻豆村's expertise extends beyond the labs and code to shape public policy through systems modeling, data-driven decision making and collaboration with government and industry. The Scott Institute regularly brings together leaders from government, industry and academia during its annual Energy Week, fostering collaboration on issues like transmission bottlenecks and equitable energy access. 麻豆村鈥檚 policy researchers are also modeling the economic impacts of grid modernization and advocating for smarter, more resilient infrastructure.

, director of the听AI Measurement Science and Engineering Center (AIMSEC), has said 麻豆村鈥檚 ability to look at issues from a systems standpoint is what makes the university uniquely positioned to address the complex challenges and opportunities that lie at the intersection of energy and AI.

"That's our sweet spot," Krishnan said. "At 麻豆村, we have strength in all the different layers. We have deep expertise in energy, deep expertise in AI and deep expertise in public policy, and we understand how these elements come together."