Latest Stories

166 results found
Filters applied: Radiological & Nuclear Detection, Graph and Data Analytics
MAY 4, 2020
Staff Accomplishment

PNNL Team Takes a Lead Role at 5G Workshop

Ten staff members from PNNL were invited to attend and lead the various breakout sessions at the Department of Energy Office of Science 5G Enabled Energy Innovation Workshop (5GEEIW), which was held in early March.
APRIL 28, 2020
Feature

The Quantum Gate Hack

PNNL quantum algorithm theorist and developer Nathan Wiebe is applying ideas from data science and gaming hacks to quantum computing
JANUARY 24, 2020
Staff Accomplishment

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.
JANUARY 10, 2020
Feature

Clark Recognized for Nuclear Chemistry Research

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.
DECEMBER 20, 2019
Staff Accomplishment

Two PNNL Researchers Named IEEE Fellows

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.
DECEMBER 17, 2019
Staff Accomplishment

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.
DECEMBER 11, 2019
Feature

PNNL to Lead New Grid Modernization Projects

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.
NOVEMBER 12, 2019
Staff Accomplishment

Driving Machine Learning to Exascale

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.