PNNL provided ultra-low measurements of argon-39 to date groundwater as part of a collaborative study of the aquifer in Californiaās San Joaquin Valley. PNNL is one of only a few laboratories worldwide with this capability.
Machine learning techniques are accelerating the development of stronger alloys for power plants, which will yield efficiency, cost, and decarbonization benefits.
Svitlana Volkova, chief scientist for decision intelligence and analytics at PNNL, was invited as a panelist at the SIAM International Conference on Data Mining
PNNL data scientists Svitlana Volkova and Emily Saldanha, along with former PNNL intern Pamela Bilo Thomas, will publish their research on online information spread in Nature's Scientific Reports.
Michael Henry, a senior data scientist at PNNL, has accepted a joint appointment at the Texas A&M University RELLIS Center for Applied Research and Experiential Learning.
PNNL data scientists Henry Kvinge and Ted Fujimoto presented their research on few-shot learning and reinforcement learning, respectively, at workshops during the 2021 AAAI Conference on Artificial Intelligence.
As a member of the NAM board of directors, Brett Jefferson, PNNL data scientist, will help lead the professional associationās mission to advance mathematical excellence of underrepresented minorities.
New Distinguished Graduate Research Program will provide opportunities for North Carolina State University doctoral students to tackle real-world data science challenges alongside PNNL scientists.
PNNL scientists joined international leaders in artificial intelligence research to discuss the latest advances, opportunities, and challenges for neural information processingāthe foundation for AI.
As a physicist at PNNL, Jon Burnettās work is about developing instruments to detect ultra-trace radionuclide signatures, analyze samples from around the world to look for evidence of nuclear explosions, and then interpret that information.