A decade-long evolution in making omics data easier to analyze earns widespread recognition.

Emilie Purvine, a chief data scientist at PNNL, was elected as a council member at large of the American Mathematical Society.

The Department of Energy, Basic Energy Sciences and Advanced Scientific Computing Research programs will support the partnership’s work on nuclear quantum behavior.

PNNL showcased its expertise in AI, machine learning, and related domains at the International Conference on Machine Learning.

The Department of Energy’s Vehicle Technologies Office recognized Livewire’s outstanding teamwork and technical expertise.

Three PNNL-affiliated researchers have been named fellows of the American Association for the Advancement of Science, the world’s largest multidisciplinary scientific society.

Tumeo will lead the ChemComp project, which was awarded for Exploratory Research in Extreme Scale Science

Stinis will serve as a principal investigator on two of the four projects selected for funding by the Advanced Scientific Computing Research program.

The award was given at the 29th International Conference on Information, Communication and Automation Technologies.

Zhijie (Jay) Xu will apply his expertise in multiscale modeling to this editorial role.

ACMD staff contributed to 30 years of atmospheric data collection for the Department of Energy’s Atmospheric Radiation Measurement user facility.

Adam Attarian led a new panel session, titled National Labs and the GEOINT Mission, at the GEOINT 2023 Symposium, held May 21–24, 2023.

Xantheas was one of four professors in 2021/2022 to be selected by the Göttingen Academy of Sciences and Humanities for this award.

Lauren Charles joins the CABI One Health Editorial Board as an associate editor.

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

Business, industry, and government careers were a focus of the PNNL-led Mathematics Research Communities conference.

Xantheas awarded a visiting fellowship from the International Center for Advanced Studies of Energy Conversion in Germany.

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

Anika Halappanavar’s research into COVID-19 misinformation earned her recognition by the Washington State Academy of Sciences as one of the state’s top high school researchers.

Researchers have been investigating if machine learning techniques could be used to help create novel beers.