Three staff selected for leadership program that brings together representatives from all 17 Department of Energy national laboratories to build the national lab leaders of tomorrow.

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

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

PNNL researchers received the “Best Paper Award” at the 39th IEEE International Conference on Computer Design.

Electrical engineer Aditya Ashok and cybersecurity researcher Thomas Edgar win best paper award for their work to create a new high-fidelity dataset that will help advance cybersecurity solutions for critical infrastructure protection.

PNNL is highlighting scientific and technical experts in the national security domain who were recently promoted to scientist and engineer level 5, one of PNNL’s most senior research roles.

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

PNNL is highlighting scientific and technical experts in the national security domain who were recently promoted to scientist and engineer Level 5, one of PNNL’s most senior research roles.

Mary Lancaster, epidemiologist and data scientist, co-authored a chapter on cyberbiosecurity for the NATO Science for Peace and Security book series.

Tumeo joins other computer scientists in a contributed article on graph processing systems to the Communications of the ACM.

DOE’s continued support will allow CENATE researchers to advance computing through the evaluation of novel technologies.

PNNL data scientist was invited to give the first big-picture talk about autonomous control systems at the Autonomous Discovery in Science and Engineering Workshop.

PNNL recognizes some of the outstanding postdoctoral researchers that move science forward during National Postdoc Appreciation Week.

PNNL computer scientist Ang Li serves as one of the principal investigators for a project selected to receive DOE funding.

When training for chemical and biological threats, in-person exercises and drills can be very limited due to the hazardous nature of the agent.

The multi-year project funded by DOE’s High Energy Physics program will focus on using machine learning to prevent power outages.

New computational modeling research provides insights into biological processes and metabolic regulation.

PNNL computer scientists joined international leaders in machine learning to present research to detect and address potential cybersecurity threats and devise epidemic interventions.

Erol Cromwell and Yan Shi, researchers at PNNL, used their backgrounds in software engineering to provide a platform for atmospheric data analysis.

PNNL data scientists Svitlana Volkova and Emily Saldanha, along with former PNNL intern Pamela Bilo Thomas, will publish their research on online information spread in Nature's Scientific Reports.