The Rapid Assessment of Platform Technologies to Expedite Response project aims to prepare against future pandemics.

To overcome high-performance computing bottlenecks, a research team at PNNL proposed using graph theory, a mathematical field that explores relationships and connections between a number, or cluster, of points in a space.

PNNL researchers use machine learning and data analytics to assist with detection of nuclear proliferation and nuclear material trafficking.

TransMED analyzes patient data from similar diseases across multiple sources to understand COVID-19 patient outcome risk factors.

PNNL experts perform fundamental climate science work at multiple scales to understand impacts on energy, water, food, and infrastructure systems.

PNNL data scientists are refining their artificial intelligence tools with COVID-19 data to advance therapeutics and treatments for a future pandemic.

A Q&A with Lauren Charles, veterinarian and PNNL data scientist, on zoonotic diseases and the role biosurveillance plays in mitigating the growing threat to global health.

Svitlana Volkova uses natural language processing and AI to reveal how misinformation and disinformation spread through social media.

Machine learning techniques are accelerating the development of stronger alloys for power plants, which will yield efficiency, cost, and decarbonization benefits.

PNNL is lending analytics expertise to a new first-of-its-kind electric-vehicle carsharing program being launched in Hood River, Oregon.

As he prepares to enter PNNL's Energy Sciences Center later this year, Vijayakumar 'Vijay' Murugesan is among DOE leaders exploring solutions to design and build transformative materials for batteries of the future.

New approach allows nonexperts to optimize control of a building's energy systems without adding computing power or proprietary software.

A research effort under the PNNL-led Battery500 Consortium solved a longtime debate surrounding a structure in lithium-metal battery anodes.

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.

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

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

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

PNNL researchers and professional staff led discussions ranging from biothreats and climate change to science careers at the 2020 annual meeting of the American Association for the Advancement of Science, held this year in Seattle.