Data-driven autonomous technology to rapidly design and deliver antiviral interventions targeting SARS-CoV-2 to reduce drug discovery timeline and advance bio preparedness capabilities.

Data scientist Jung Lee accepted the position of review editor for Frontiers in Computational Neuroscience after serving as a guest editor for a special issue.

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

PNNL lighting expert Andrea Wilkerson will serve an initial two-year term on the editorial board of LEUKOS journal.

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.

Lili Yao named associated editor at the Journal of Hydrology, a leading journal in the field of hydrological sciences.

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.

PNNL’s Karma Sawyer has been named a Distinguished Gilbreth Speaker by the National Academy of Engineering.

Extreme winter storms are growing wetter and changing shape in the Western United States—such changes could compromise infrastructure designed to withstand only so much water.

Staff at PNNL recently completed a report highlighting commercial products enabled through projects funded by the Department of Energy’s Building Technologies Office.

PNNL researchers launch a new DOE project focused on advancing GUV technology for improved public health outcomes and decarbonization benefits.

PNNL mathematician Aaron Luttman contributed to the organizing committee for workshop exploring robust machine learning and artificial intelligence systems for the U.S. Army.

STEM Education programs at DOE and national labs offer environmental management internships; applications are due soon for summer 2023.

New PNNL research makes it easier to differentiate between chemical and nuclear explosions.

The Simple Building Calculator, developed at PNNL, meets a need for a quick, interactive, and economic method to evaluate energy use—and potential savings from efficiency measures—in simple commercial buildings.

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.

Researchers developed a machine learning model that can analyze chemical reactions as they happen in an electron microscope.

PNNL-Sequim team wins ESTCP Project of the Year for their work supporting underwater munition remediation.

Steven Spurgeon’s research is featured in the cover of the MRS Bulletin along with his team’s invited perspective on the future of machine learning for electron and scanning probe microscopy.