Ryan King

Ryan King is a senior researcher at the National Renewable Energy Laboratory (NREL), focusing on optimization, machine learning, and uncertainty quantification applied to energy systems and turbulent flows. He leads projects involving physics-informed deep learning for wind energy systems, wind farm modeling, and multi-fidelity uncertainty quantification.

His educational background includes a PhD in Mechanical Engineering from the University of Colorado and a Bachelor's from MIT. He has worked on over 750 MW of wind energy projects prior to his research role.

Key research interests include turbulent flows, deep learning applications in energy, stochastic optimization, and adjoint methods. He has received the NREL Outstanding Mentor Award in 2018 and 2019.

His work bridges computational science with energy innovation, addressing challenges in wind farm design, climate change impacts, and renewable energy systems through advanced AI and data-driven methodologies.