Deep learning helps make predictions on the effects of the El Niño-Southern Oscillation on river flows more accurate.

PNNL welcomes new joint appointments to expand the research productivity and scientific impact of both PNNL and the university partners, broadening the base of expertise at each institution and helping to build interdisciplinary teams.

Artificial intelligence may help humans and computers work together to monitor materials that could be used to make weapons.

PNNL researchers combined deep operator networks with spectral methods to efficiently and accurately solve complex equations.

Report for the Oregon Public Utility Commission highlights innovations and best practices for resilience and utility planning could be helpful to other states as well.

The Building and Environment journal named Drgoňa’s co-authored work one of 2022’s best papers.

Exploring why some brains are more resilient to the impact of Alzheimer’s disease could lead to improved diagnoses, treatment and prevention.

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

Samantha Erwin was one of six speakers during the Careers Using Mathematics panel at the Nebraska Conference for Undergraduate Women in Mathematics.

The work by the team at PNNL takes a critical step in leveraging ML to accelerate advanced manufacturing R&D, specifically for manufacturing techniques without access to efficient, first-principles simulations.

For a second year in a row, doctoral intern Jack Watson was awarded the Student Merit Award by the Society for Risk Analysis and the Resilience Analysis Specialty group.

To thwart pathogens, researchers in the epidemiology field of infectious disease (ID) prediction are continuously trying to forecast when, where, and how an ID event will occur.

PNNL gathered researchers from eight national laboratories plus the U.S. Department of Energy (DOE) to share ideas and build synergy at the Energy Equity and Environmental Justice Summit.

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

HiSVSIM enables large-scale quantum simulations through graph partitioning.

PNNL computational neuroscientist Rogene Eichler West honored with the International Society for Neuroregulation & Research Joseph and Ann Marie Horvat Distinguished Service Award.

PNNL joint appointee Auroop Ganguly uses data science to study the impacts of climate change.

Scientists at PNNL are working to better prepare authorities, emergency responders, communities and the grid in the face of increasingly extreme hurricanes.

A new web-based tool provides easy-to-understand progress metrics and other data about groundwater cleanup sites overseen by the DOE Office of Environmental Management.

Scientists are pioneering approaches in the branch of artificial intelligence known as machine learning to design and train computer software programs that guide the development of new manufacturing processes.