Data scientist Jung Lee accepted the position of review editor for Frontiers in Computational Neuroscience after serving as a guest editor for a special issue.
The work by the team at PNNL takes a critical step in leveraging ML to accelerate advanced manufacturing R&D, specifically for manufacturing techniques without access to efficient, first-principles simulations.
PNNL mathematician Aaron Luttman contributed to the organizing committee for workshop exploring robust machine learning and artificial intelligence systems for the U.S. Army.
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.
PNNL gathered researchers from eight national laboratories plus the U.S. Department of Energy (DOE) to share ideas and build synergy at the Energy Equity and Environmental Justice Summit.
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.
Top scientists and officials from government, academia, Alaskan Native communities, and industry are heading to Alaska to focus on driving energy technologies for a more sustainable Arctic region.
To support federal energy agencies in meeting renewed environmental policies, PNNL is identifying the mechanisms and practices that could enhance agencies’ existing environmental justice programs, policies, and activities.