PNNL-developed Water Balance Tool estimates consumption for major water end-uses. Understanding the breakout of water use identifies water efficiency opportunities and allows facility managers to spot potential system losses.

New Distinguished Graduate Research Program will provide opportunities for North Carolina State University doctoral students to tackle real-world data science challenges alongside PNNL scientists.

Joseph Williams, PNNL Seattle Research Center director, was elected chair of the Institute of Electrical and Electronic Engineer’s Seattle section.

New mathematical tools developed at PNNL hold promise to transform the way we operate and defend complex cyber-physical systems, such as the power grid.

The partnership to apply artificial intelligence to improve complex systems is part of a U.S. Department of Energy Office of Science $4.2 million, three-year grant.

PNNL scientists joined international leaders in artificial intelligence research to discuss the latest advances, opportunities, and challenges for neural information processing—the foundation for AI.

Red teaming for CPS, the process of challenging systems, involves a group of cybersecurity experts to emulate end-to-end cyberattacks following a set of realistic tactics, techniques, and procedures.

Buildings account for around 40 percent of our nation's energy use and consume 75 percent of our nation’s electricity each year. Energy use is also one of the biggest costs for facility owners.

Data Scientist Sam Chatterjee to chair security and defense specialty group of the Society for Risk Analysis.

David Manz is a cybersecurity researcher who is working with cyber-physical systems to better protect the critical infrastructure.

Long-term PNNL support has helped enable the continued success of the Chesapeake Large-Scale Analytics Conference.

As COVID-19 was limiting in-person contact, halting travel, and creating additional barriers, researchers at PNNL were working to find solutions on how they could still get work done while establishing new safety protocols.

PNNL’s longstanding grid and buildings capabilities are driving two projects that test transactive energy concepts on a grand scale and lay the groundwork for a more efficient U.S. energy system.

PNNL researchers have shown an improved binarized neural network can deliver a low-cost and low-energy computation to help the performance of smart devices and the power grid.

The project received an Innovative and Novel Computational Impact on Theory and Experiment (INCITE) award, a highly competitive U.S. Department of Energy Office of Science program.

PNNL data scientists Ján Drgoňa and Draguna Vrabie are working to reduce deployment costs of advanced energy control systems for buildings.

PNNL and Microsoft Quantum partner to link quantum circuits to powerful government supercomputers.

Researchers at PNNL have developed a bacteria testing system called OmniScreen that combines biological and synthetic chemistry with machine learning to hunt down pathogens before they strike.

PNNL’s new Smart Power Grid Simulator, or Smart-PGSim, combines high-performance computing and artificial intelligence to optimize power grid simulations without sacrificing accuracy.

The MIT-sponsored competition encourages community approaches to developing new solutions for analyzing graphs and sparse data; PNNL has placed a winner in each year.