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.
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.
Eric Hoppe, senior scientist, was selected a 2019 American Chemical Society (ACS) fellow. Eric is being recognized for his contributions to analytical chemistry measurements and three decades of volunteer service to the ACS community.
PNNL Laboratory Director Steve Ashby attended an event marking the 20th anniversary of the Department of Energy’s National Nuclear Security Administration Nuclear Smuggling Detection and Deterrence program.
Network Collapse, a virtual reality science, technology, engineering, and mathematics (STEM) app developed by PNNL researchers, has won a Gold Award from the 2019 International Serious Play Award.
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.
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.