The Center for Continuum Computing at PNNL aims to integrate cloud platforms, high-performance computing, and edge devices into a seamless ecosystem that accelerates scientific discovery.

Lauren Charles, a chief data scientist at PNNL, showcased the vital research coming out of her program at The National Academies Forum workshop in Washington, D.C., January 15–16, 2025.

PNNL’s Center for Cloud Computing is addressing challenges in data management and hybrid cloud solutions with industry and academic partnerships.

PNNL biodefense experts seek to identify, understand and mitigate the risks of biological pathogens—whether naturally occurring or intentionally created—so steps can be taken to prepare and respond.

In a recent publication in Nature Communications, a team of researchers presents a mathematical theory to address the challenge of barren plateaus in quantum machine learning.

Researchers will explore climate, pathogens and energy-efficient microelectronics using 3 million node hours on the nation’s supercomputers.

Research at PNNL and the University of Texas at El Paso are addressing computational challenges of thinking beyond the list and developing bioagent-agnostic signatures to assess threats.

Beyond melting ice and higher temperatures: On Earth Day, scientists consider how climate change will affect national security.

Scientists have developed a better way to recognize denial-of-service internet attacks, improving detection by 90 percent.

PNNL researchers outline open problems in different scientific areas in the Journal of Combinatorics.

Researchers have knitted together three large databases of information to help cybersecurity experts detect and prevent attacks.

Scientists have taken a key step toward harnessing a form of AI known as deep reinforcement learning to protect computer networks.

Microbes that were previously frozen in soils are becoming more active. This study demonstrates the diverse RNA viral communities found in thawed permafrost.

HiSVSIM enables large-scale quantum simulations through graph partitioning.

Scientists can detect the virus that causes COVID-19 by using a bubble that spills its contents like a piñata when encountering the virus.

James Ang, John Feo, and Marco Minutoli organized a high performance computing workshop at the prestigious ISC High Performance 2022 conference.

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

The virus that causes COVID-19 takes over the body’s fat-processing system and boosts cellular triglycerides as it causes disease.

PNNL scientists publish paper and host workshops to share threat-agnostic vision for biodefense.

PNNL researchers contributed to the International Conference on Data Science and Advanced Analytics 2021 Best Paper Award-winning publication.