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 licensed two technologies to generate hydrogen. One, a reactor design, generates hydrogen from natural gas. The second innovation uses a 3D printing method to economically manufacture the generator.

Electrical engineer Tom McDermott has been named the winner of a power distribution engineering award.

PNNL is developing the Digital Twins for Hydropower framework to help the industry to affordably modernize the aging hydropower fleet.

Aaron Luttman, a mathematician and senior technical advisor at PNNL, was invited as a guest speaker during the 2021 National Math Festival.

In the face of the COVID-19 pandemic, PNNL pivoted to online learning approaches to conduct critical national security training across the globe.

PNNL researchers are using explainable artificial intelligence to develop new ways to understand and interpret data for national security.

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.

Study says planners need to account for climate impacts on renewable energy during capacity development planning to fully understand investment implications to the power sector.

Three unused, 48,000-pound stainless steel canisters arrived at PNNL, bringing the chance to deepen research in spent nuclear fuel storage and transportation.

Joint appointee and chief scientist for the Solid Phase Processing Science Initiative at PNNL Suveen Mathaudhu has been awarded a Brimacombe Medal by The Minerals & Materials Society.

Explainable artificial intelligence—understanding and explaining the reasoning behind AI decisions—is a necessity for national security.

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.

Explainable AI helps scientists understand and untangle the threads of information that the system uses to make choices or recommendations.

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 association’s mission to advance mathematical excellence of underrepresented minorities.

In 2020, virtual Washington State University teams successfully worked together in a program sponsored by the National Nuclear Security Administration’s (NNSA) Office of International Nuclear Safeguards.

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.

New approach allows nonexperts to optimize control of a building's energy systems without adding computing power or proprietary software.

PNNL researchers simulated residential battery use and found in-home energy storage can benefit both the power grid and homeowners.