Contributions from researchers across Pacific Northwest National Laboratory (PNNL) were recently recognized in the preliminary findings of a Secretary of Energy Advisory Board (SEAB) report.

A 2011 earthquake and tsunami in Japan that knocked out a nuclear power plant helped inspire PNNL computational scientists looking for clues of future nuclear reactor mishaps by tracking radioactive iodine.

Ang Li and Antonino Tumeo will present hardware to balance machine learning workloads at a top computer architecture conference.

PNNL’s Patrick Balducci delivered an information-packed tutorial on grid energy storage valuation at the Naval Postgraduate School in Monterey, California.

PNNL quantum algorithm theorist and developer Nathan Wiebe is applying ideas from data science and gaming hacks to quantum computing

Artificial intelligence helps researchers identify metabolites, the small molecules that underlie life.

Verizon recently announced a partnership that will make Pacific Northwest National Laboratory the U.S. Department of Energy’s first national laboratory with Verizon 5G ultra wideband wireless technology.

Combining its strength in biological sciences and data analytics, researchers at the Department of Energy's PNNL are working to enable a quick response to a biological incident — whether intentional, accidental or natural.

PNNL researchers and professional staff led discussions ranging from biothreats and climate change to science careers at the 2020 annual meeting of the American Association for the Advancement of Science, held this year in Seattle.

First-of-its-kind network analysis on a supercomputer can speed real-time applications for cybersecurity, transportation, and infectious disease tracking

In a special edition of the Journal of Information Warfare, Pacific Northwest National Laboratory researchers explore the revolution of technologies defending the nation’s critical infrastructure.

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.

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.

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.

With support from DOE’s Office of Electricity and National Grid, PNNL led a groundbreaking study to accurately assess the full value of grid energy storage investments across a wide variety of use cases.

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.

Energy storage is slowly shifting utility planning practices from the current paradigm, which ensures grid reliability by building reserve generation resources, to ensuring grid reliability by optimizing grid services.