At a conference featuring the most advanced computing hardware and software, ML in its various guises was on full display and highlighted by Nathan Baker’s featured invited presentation.

From microscopic bacteria in river sediments to vast watersheds to global-scale data and inquiries, a PNNL scientist plays a big research role

PNNL’s Intelligent Load Control technology manages and adjusts electricity use in buildings when there’s peak demand on the power grid.

A new approach developed by PNNL scientists improves the accuracy of patient diagnosis up to 20 percent when compared to other embedding approaches.

Scientists at PNNL are bringing artificial intelligence into the quest to see whether computers can help humans sift through a sea of experimental data.

The U.S. Department of Energy’s Pacific Northwest National Laboratory (PNNL) is the recipient of two R&D 100 awards and one gold medal.

We are all citizens of watersheds, the terrestrial landscapes that determine how much water we have, how clean it is, where it goes, and how fast.

In today’s digital age, the rabbit hole of connected information can be not only a time sink, but downright overwhelming. Even for high-performance computers.

Twenty-four analysts from U.S. intelligence organizations met in August for a machine learning activity with PNNL researchers Nicole Nichols, Jeremiah Rounds, Lawrence Phillips, and Brian Kritzstein.

Three powerhouses in the realm of artificial intelligence have become partners in a new research center created by the U.S. Department of Energy.

A PNNL technology enables automated Economic Dispatch, which coordinates the use of energy in a manner that enhances distributed generation, efficiency, renewables, and grid reliability.

Trouble on the electric grid might start with something relatively small: a downed power line, or a lightning strike at a substation. What happens next?

Pacific Northwest National Laboratory is leading efforts to address next-generation computing’s critical role in protecting the nation from cybersecurity threats.

Researchers at PNNL are applying deep learning techniques to learn more about neutrinos, part of a worldwide network of researchers trying to understand one of the universe’s most elusive particles.

A PNNL researcher peers into the future and sees homes and neighborhoods seamlessly working together to coordinate energy use.

Scientists created a fast-track tutorial that equips a neural network to tackle drug discovery and other applications where there's a shortage of precisely labeled chemical data.

Researchers at PNNL are developing a new class of acoustically active nanomaterials designed to improve the high-resolution tracking of exploratory fluids injected into the subsurface. These could improve subsurface geophysical monitoring.

"It's sort of like using infrared goggles to see heat signatures in the dark, except this is underground." PNNL and CHPRC implemented a state-of-the-art approach to monitor the process of remediating residual uranium at Hanford's 300 Area.