Women in Computational Topology Success
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 Scientists Author Top Cited Paper
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.
Nicole Nichols Speaks at AI Summit
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.
PNNL and Other National Labs Share Grid Modernization Work at DistribuTECH International
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.
AI Ups Response Time when the Grid Goes Down
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?
PNNL, Sandia, and Georgia Tech Join Forces in AI Effort
Three powerhouses in the realm of artificial intelligence have become partners in a new research center created by the U.S. Department of Energy.
Teams of Rivals: PNNL and LAS Collaborate on Machine Learning
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.
Using Deep Learning as a Searchlight for Dark Matter
Scientists at PNNL are bringing artificial intelligence into the quest to see whether computers can help humans sift through a sea of experimental data.
PNNL Garners R&D 100 Awards
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.
New AI Model Tries to Synthesize Patient Data Like Doctors Do
A new approach developed by PNNL scientists improves the accuracy of patient diagnosis up to 20 percent when compared to other embedding approaches.