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.

The Marine and Coastal Research Laboratory (MCRL), part of PNNL, in Sequim, Washington, is the U.S. Department of Energy’s only marine research facility. It has a rich history and expanding research scope.

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

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

PNNL researchers established an Internet of Things Common Operating Environment (IoTCOE) laboratory to explore the risks associated with IoT connectivity to the internet, the energy grid and other critical infrastructures.

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

The PNNL-developed VOLTTRON™ software platform’s advancement has benefited from a community-driven approach. The technology has been used in buildings nationwide, including most recently on a university campus.

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 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.

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.

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.

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.

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

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

Artificial intelligence helps researchers identify metabolites, the small molecules that underlie life.

PNNL employs deep learning strategies to advance Model Predictive Control (MPC), a highly promising solution for intelligent building operations.