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 research analysist specializing in biological and chemical weapons nonproliferation invited to join editorial board for Frontiers in Microbiology.
PNNL mathematician Aaron Luttman contributed to the organizing committee for workshop exploring robust machine learning and artificial intelligence systems for the U.S. Army.
Researchers at PNNL leveraged their experiences to connect with attendees at the 2022 SACNAS National Diversity in STEM Conference, October 27–29, 2022, in San Juan, Puerto Rico.
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.
Advancing the science of radiation, especially among students at minority-serving institutions, is the goal of one of the Department of Energy’s newest consortia.
Kate Doty was invited to lend her expertise as guest editor for the International Journal of Nuclear Security on a special issue on women in nuclear security.
Twenty years after the first radiation portal monitor was installed, PNNL continues supporting the Department of Homeland Security’s efforts to detect and prevent terrorist weapons from crossing our borders.
PNNL research, featured on the cover of two science journals, describes advancements in using Raman spectrometry for Hanford Site nuclear waste remediation.
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.
