PNNL mathematician Aaron Luttman contributed to the organizing committee for workshop exploring robust machine learning and artificial intelligence systems for the U.S. Army.
A multi-institutional team of wind energy experts led by PNNL assessed the scientific grand challenges for offshore wind and provided recommendations for closing gaps in models.
Steven Spurgeon’s research is featured in the cover of the MRS Bulletin along with his team’s invited perspective on the future of machine learning for electron and scanning probe microscopy.
As leaders in AI and machine learning, PNNL experts are sharing their latest findings at the 36th annual Neural Information Processing Systems (NeurIPS) Conference, Nov. 28–Dec. 9, 2022.
Scientists are pioneering approaches in the branch of artificial intelligence known as machine learning to design and train computer software programs that guide the development of new manufacturing processes.
Recognizing how innovation and clean technologies at the very edge of the grid can work together to transition the electricity system, PNNL takes a multidisciplinary approach to advancing and integrating renewable energy solutions.
PNNL Chief Scientist for Computing Jim Ang will be part of a DOE Office of Science virtual discussion regarding industry collaborations on AI hardware.
PNNL data scientist to edit collection of research articles focused on understanding how microcircuits function in the brain and in artificial intelligence systems.
A paper co-authored by Courtney Corley was recently selected as the most influential paper for the Twenty-First National Conference on Artificial Intelligence.