Welcome!

I’m Hilary Egan, a computational data scientist at the National Renewable Energy Laboratory. My work focuses on leveraging applied AI and computational science to address critical challenges across renewable energy domains. This includes developing intelligent methods to bridge the gap between high-performance simulations and experimental results, enhancing the energy efficiency and grid integration of data centers, and developing autonomous laboratory technologies. Beyond my technical work, I also actively contribute to AI policy and strategy initiatives focused on ensuring the responsible & impactful deployment of AI technologies at NREL and within the DOE.

I hold a Bachelor’s degree in Physics from Michigan State University and a PhD in Astrophysics and Planetary Science from the University of Colorado Boulder. Outside of work I enjoy all sorts of classic Colorado activities including rock climbing, mountain biking, and skiing – though I’ll never say no to a good book either.

If you are a scientist, student, or potential collaborator interested in applying AI & computational science in renewable energy relevant domains, please reach out!

Computational Research Interests

• Deep learning
• High-performance computing
• Multi-fidelity methods
• Uncertainty quantification
• Differentiable simulations
• Autonomous, scalable workflows
• Digital Twins

Domain Applications

• Materials Synthesis and Characterization
• Building Technologies
• Biofuels & Bioenergy
• Plasma Physics