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20172025

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Hilary Egan's work focuses on leveraging applied artificial intelligence (AI) and computational science to address critical challenges across renewable energy domains. Key research areas include developing AI methods to connect high-performance computing simulations with experiments, improving the energy efficiency and grid integration of data centers, and advancing autonomous laboratory technologies.

Research Interests

Deep learning

High-performance computing

Multi-fidelity methods

Uncertainty quantification

Statistical inference

Differentiable simulations

Education/Academic Qualification

Bachelor, Physics, Michigan State University

PhD, Astrophysics and Planetary Science, University of Colorado Boulder

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Collaborations and Top Research Areas From the Past 5 Years

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