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

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.

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

The workshop brought together 184 scientists to explore research opportunities for nuclear physics in artificial intelligence.

PNNL computational biologists, structural biologists, and analytical chemists are using their expertise to safely accelerate the design step of the COVID-19 drug discovery process.

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

Using public data from the entire 1,500-square-mile Los Angeles metropolitan area, PNNL researchers reduced the time needed to create a traffic congestion model by an order of magnitude, from hours to minutes.

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.

Ken Geelhood is a nuclear engineer who is studying how the challenging conditions of a nuclear reactor affect the reliability of fuel.

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 developed a new tool that combines artificial intelligence and microscopy data to rapidly test new materials for fusion reactor use.

Pacific Northwest National Laboratory researchers developed a graphical processing unit (GPU)-centered quantum computer simulator that can be 10 times faster than any other quantum computer simulator.

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.

Infusing data science and artificial intelligence into electron microscopy could advance energy storage, quantum information science, and materials design.

Tracking down nefarious users is just one example of work at PNNL’s Center for Advanced Technology Evaluation, a computing proving ground supported by DOE’s Advanced Scientific Computing Research program.