PNNL computing experts Robert Rallo and Court Corley contribute their knowledge to a recent DOE report on applications of AI to energy, materials, and the power grid.

New methodological approach demonstrates how to assess the economic value, including non-traditional value streams, of converting non-powered dams to hydroelectric facilities.

New research identifies the most important factors in successful fish passage, pointing toward new options for flexible dam operations.

PNNL scientists have put forth a new approach to protect the electric grid, creating an approach that sorts and prioritizes cyber threats on the fly.

Pacific Northwest National Laboratory launches the Training Outreach and Recruitment for Cybersecurity Hydropower program at the University of Texas at El Paso.

Visual Sample Plan, a free software tool developed at PNNL that boosts statistics-based planning, has been recognized with a 2024 Federal Laboratory Consortium Award.

Researchers created a methodology to design custom network topologies that improve the execution time for scientific applications.

Adam Roberts has been named a scientist and engineer level 5 in the national security domain.

Thomas Edgar has been named a scientist and engineer level 5 in the national security domain.

Doug Nordwall has been named a scientist and engineer level 5 in the national security domain.

Tumeo will lead the ChemComp project, which was awarded for Exploratory Research in Extreme Scale Science

Developed with community input, the new Hydropower Vision Roadmap lays out a path to achieve a shared vison for modern hydropower by 2050.

Stinis will serve as a principal investigator on two of the four projects selected for funding by the Advanced Scientific Computing Research program.

Researchers unveil user-friendly software to keep complex projects on budget and on schedule.

The Rapid Assessment of Platform Technologies to Expedite Response project aims to prepare against future pandemics.

The award was given at the 29th International Conference on Information, Communication and Automation Technologies.

Zhijie (Jay) Xu will apply his expertise in multiscale modeling to this editorial role.

PNNL researchers present challenges and opportunities for fusing graph neural networks with deep reinforcement learning.

ACMD staff contributed to 30 years of atmospheric data collection for the Department of Energy’s Atmospheric Radiation Measurement user facility.

PNNL researchers outline open problems in different scientific areas in the Journal of Combinatorics.