Filtered by Data Analytics & Machine Learning, Grid Cybersecurity, Scientific Discovery, Solar Energy, Subsurface Energy Systems, and Subsurface Science
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.
Seventeen teams from regional colleges and universities gathered at PNNL Nov. 16 to put their cyber skills to the test by protecting critical energy infrastructure against simulated cyberattacks as part of DOE's CyberForce Competition.
Global climate change is often at the forefront of national and international discussions and controversies, yet many details of the specific contributing factors are poorly understood.
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.
More than 350 people from scientific institutions, education and the private sector gathered at the PNNL campus July 30 for the IEEE Women in Engineering International Leadership Summit.
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.
PNNL scientists have taken one of the most in-depth looks ever at the riot of protein activity that underlies colon cancer and have identified potential new molecular targets to try to stop the disease.
In one of the largest blockchain grid-cyber projects of its kind, PNNL is working with a network of industry partners to test and demonstrate blockchain’s ability to increase the cybersecurity resilience of power grid.