Nicole Nichols, a senior researcher at PNNL, spoke during the AI: Policy Matters Summit in Seattle, Washington on December 12. The summit, hosted by TechAlliance, brought together more than 200 leaders from across Washington State.

Two PNNL data scientists, Lauren Charles and Courtney Corley, were authors for one of the top 10 percent most cited PLOS ONE papers published in 2015.

The world’s largest scientific society honored Sue B. Clark, a PNNL and WSU chemist, for contributions toward resolving our legacy of radioactive waste, advancing nuclear safeguards, and developing landmark nuclear research capabilities.

Sonja Glavaski and Kevin Schneider, both electrical engineers at PNNL, have been named as IEEE fellows. IEEE is the world's largest technical professional organization dedicated to advancing technology for the benefit of humanity.

A group of female mathematicians and computer scientists, which includes PNNL’s Emilie Purvine, has published its third paper on joint research to understand and accurately represent object relationships through metric graphs.

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.

PNNL’s Nuclear Process Science Initiative (NPSI) has developed a book that examines processes used to separate nuclear materials.

WSU recently announced James Boncella will lead the WSU-PNNL Nuclear Science and Technology Institute.

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.

PNNL and Argonne researchers developed and tested a chemical process that successfully captures radioactive byproducts from used nuclear fuel so they could be sent to advanced reactors for destruction while also producing electrical power.

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

Through her role in the Department of Energy’s Advanced Scientific Computing Research-supported ExaLearn project, Jenna Pope is developing deep learning approaches for finding optimal water cluster structures for a variety of applications.

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.

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 gathering of international experts in Portland, Oregon, explored the future of electron microscopy and surfaced potential solutions in areas including new instrument designs, high-speed detectors, and data analytics capabilities.

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.