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.
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.
As a physicist at PNNL, Jon Burnett’s work is about developing instruments to detect ultra-trace radionuclide signatures, analyze samples from around the world to look for evidence of nuclear explosions, and then interpret that information.
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.
Project manager Larry Morgan has spent half a century at Pacific Northwest National Laboratory—marking one of the longest tenures in the laboratory’s history.
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.
Rey Suarez was the keynote speaker at the Preparatory Commission of the Comprehensive Nuclear-Test-Ban Treaty Organization’s Specialized Technical Meeting on Preventive and Predicative Maintenance of the International Monitoring 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.