PNNL scientists have created a tool called WatchOwl to collect more than 4 million tweets per day related to the COVID-19 pandemic. The tool analyzes tweets related to interventions like social distancing and movement restrictions.

Embedding the known physics of the system to be controlled in the AI model of the system is data efficient and provides safety guarantees.

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.

PNNL is managing the Data Archive and Portal, which provides the wind research community with secure, timely, easy, and open access to all data brought in from research under DOE’s Atmosphere to Electrons program.

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.

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.

PNNL and the 13 other national laboratories of the Grid Modernization Laboratory Consortium (GMLC) will be sharing their R&D work and technologies for grid modernization at DistribuTECH International in San Antonio Jan. 28-30.

PNNL will lead three new grid modernization projects funded by the Department of Energy. The projects focus on scalability and usability, networked microgrids, and machine learning for a more resilient, flexible and secure power grid.

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.

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

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.

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.