PNNL data scientists Henry Kvinge and Ted Fujimoto presented their research on few-shot learning and reinforcement learning, respectively, at workshops during the 2021 AAAI Conference on Artificial Intelligence.

As a member of the NAM board of directors, Brett Jefferson, PNNL data scientist, will help lead the professional association’s mission to advance mathematical excellence of underrepresented minorities.

PNNL physicist Jan Strube is defining experimental requirements to track high-energy particles at the proposed International Linear Collider.

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.

PNNL researchers simulated residential battery use and found in-home energy storage can benefit both the power grid and homeowners.

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.

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

Connected moments math shortcut shaves time and cost of quantum calculations while maintaining accuracy.

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.

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.

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.