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Power Shift: How CMU Is Leading America’s Energy Evolution

In the heart of Pittsburgh, a quiet revolution is underway.

Associate Professor and Director of Machine Learning

Assistant Professor, Computer Science

University Professor

Trustees Professor of Security and Technology Director, Carnegie Mellon Institute for Security and Technology

Professor, Electrical and Computer Engineering

Department Head Professor, Electrical and Computer Engineering

 Carnegie Mellon University, long known for its prowess in computer science and engineering, is now emerging as a key innovator within America’s 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 As AI models grow more powerful, so too does their appetite for energy, straining an aging and outdated grid and prompting urgent questions about infrastructure, security and access.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, CMU researchers are working on practical solutions to pressing challenges in how the U.S. produces, moves and secures energy.

Learn what CMU experts have to say about their Work That Matters.

 

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CMU Experts at the Intersection of Energy and Innovation

Director of Studies, Washington Office, Carnegie Mellon Institute for Strategy & Technology

Associate Professor

Associate Professor, Financial Economics

Professor

Research Professor, Robotics Institute

Dean, College of Engineering

  Carnegie Mellon University experts are developing practical solutions for a fast-changing energy system. Their work modernizes infrastructure, accelerates innovation and harnesses AI for a more efficient and resilient future at a moment when the stakes for national competitiveness and public well-being have never been higher. 

Learn what CMU experts have to say about their Work That Matters.

 

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Artificial Intelligence Makes Energy Demand More Complex — And More Achievable

Artificial intelligence, a field known for its expanding uses across society, is also increasingly notorious for the massive amount of energy it needs to function.

Trustee Professor of Civil and Environmental Engineering

  In a 2024 paper, researchers from Carnegie Mellon University and machine learning development corporation Hugging Face found that generative AI systems could use as much as 33 times more energy to complete a task than task-specific software would.

“The climate and sustainability challenge can be overwhelming in the amount of new clean technology that we have to deploy and develop, and the ways that the energy system has to evolve,” said Costa Samaras, head of the university-wide Wilton E. Scott Institute for Energy Innovation. “The scale of the challenge alone can be overwhelming to folks.”

However, Carnegie Mellon University’s standing commitment to the United Nations' Sustainable Development Goals and its position as a nationally recognized leader in technologies like artificial intelligence mean that it is uniquely positioned to address growing concerns around energy demand, climate resilience and social good.

 

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