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.

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.

Five staff members from PNNL received awards from the Department of Energy’s Federal Energy Management Program for contributions to projects for the U.S. Army.

As leaders in AI and machine learning, PNNL experts are sharing their latest findings at the 36th annual Neural Information Processing Systems (NeurIPS) Conference, Nov. 28–Dec. 9, 2022.

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

A new version of the Department of Energy’s Technical Resilience Navigator allows users to prioritize resilience solutions based on both risk reduction and emissions impact.

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.

In honor of National Intern Day, PNNL and intern Jonathan Mills were named among the Top 100 in the nation by early-career recruiting firm WayUp.

PNNL researchers teamed up with SambaNova to enhance artificial intelligence for scientific computing.

As wildfires grow increasingly severe, PNNL researchers are working to slow their spread and mitigate their harmful effects.

Researchers studied water cycling to assess the achievability of net-zero water usage at military installations in the Pacific Islands.

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

PNNL researchers design an artificial intelligence-guided electron microscope in a Laboratory Directed Research and Development study.

Arun Veeramany furthers the field of risk, reliability, and resilience in civil and mechanical engineering in his new role as an American Society of Civil Engineers-American Society of Mechanical Engineers journal editorial board member.

Sue Southard's one thousand dives as a PNNL staff member leave a ripple effect on efforts to keep our ocean healthy, our economy thriving, and our waters safe.

Parallel graph neural networks identify protein-ligand 3-D structural interactions to aid in protein function prediction and drug discovery.

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

PNNL Chief Scientist for Computing Jim Ang will be part of a DOE Office of Science virtual discussion regarding industry collaborations on AI hardware.

PNNL data scientist to edit collection of research articles focused on understanding how microcircuits function in the brain and in artificial intelligence systems.