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.

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

PNNL has published a report that sets the foundation for modeling gaps and technical challenges in optimizing hydropower operations for both energy production and water management.

California and other areas of the U.S. Southwest may see less future winter precipitation than previously projected by climate models, according to new research that corrects for a long-standing model error: the double-ITCZ bias.

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

Water and energy researchers are invited to join a new task force as a way to collaborate broadly on the intersection of the two topics. The task force is part of IEEE's Power and Energy Society and was launched by PNNL and UU researchers.

PNNL and the Georgia Institute of Technology vow to collaborate more impactfully and more often in a new MOU announced October 23, 2020.

PNNL has earned “Best Paper” at an international resilience conference for research on hydropower’s capabilities and constraints in the event of extreme events, like hurricanes and rolling blackouts.

Pacific Northwest National Laboratory (PNNL) researchers pioneer a new tool to represent cellular response to viral infection.

Culminating 10 years of study, researchers at PNNL’s Marine and Coastal Research Laboratory developed a new predictive framework for estuarine–tidal river research and management.

Embedding the known physics of the system to be controlled in the AI model of the system is data efficient and provides safety guarantees.

PNNL biologists have developed a more efficient way to estimate salmon survival through dams that uses solid science but saves over 42 percent of the cost.

A PNNL research team compared two types of pumped storage hydropower (open and closed loop) to identify potential environmental impacts.

PNNL data scientists Maria Glenski and Svitlana Volkova have contributed a chapter to a book titled Disinformation, Misinformation, and Fake News in Social Media: Emerging Research Challenges and Opportunities.

PNNL is managing the Data Archive and Portal, which provides the wind research community with secure, timely, easy, and open access to all data brought in from research under DOE’s Atmosphere to Electrons program.

Two PNNL team members, Courtney Corley, a data scientist, and Kyle Bingman, an advisor on assured artificial intelligence (AI), were featured on a recent episode of the U.S. Department of Energy Direct Currents podcast.

We all have heard our share of fish tales, but did you know that how fish hear can tell a story of their lives?

Ten staff members from PNNL were invited to attend and lead the various breakout sessions at the Department of Energy Office of Science 5G Enabled Energy Innovation Workshop (5GEEIW), which was held in early March.

Two PNNL researchers are helping define the future of transparency and accountability for public and private use of autonomous and intelligent systems.

PNNL quantum algorithm theorist and developer Nathan Wiebe is applying ideas from data science and gaming hacks to quantum computing