Electrical engineer Aditya Ashok and cybersecurity researcher Thomas Edgar win best paper award for their work to create a new high-fidelity dataset that will help advance cybersecurity solutions for critical infrastructure protection.

PNNL researchers contributed to the International Conference on Data Science and Advanced Analytics 2021 Best Paper Award-winning publication.

DOE’s continued support will allow CENATE researchers to advance computing through the evaluation of novel technologies.

PNNL computer scientist Ang Li serves as one of the principal investigators for a project selected to receive DOE funding.

With a focus on prevention, PNNL researchers are working to predict droughts, enhance grid resilience, and manage forests to reduce wildfire.

Researchers to design their own computer accelerators for faster analysis of large datasets.

PNNL is developing the Digital Twins for Hydropower framework to help the industry to affordably modernize the aging hydropower fleet.

PNNL computer scientists joined international leaders in machine learning to present research to detect and address potential cybersecurity threats and devise epidemic interventions.

Sriram Krishnamoorthy, a computer scientist at PNNL, collaborated with a University of Utah team on a student computing research project that won Best Student Paper at SC20.

James A. Ang, a PNNL computing expert, was recently invited to moderate a panel in a virtual workshop focused on federally funded research and development on software for heterogeneous computing.

A PNNL research team compared two types of pumped storage hydropower (open and closed loop) to identify potential environmental impacts.

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.

Researchers at PNNL used key metrics to develop visualizations that show how the combined effects of climate change on hydropower and load influence the frequency, duration, and severity of power shortfalls.