PNNL researchers have published their paper, “Introducing Molecular Hypernetworks for Discovery in Multidimensional Metabolomics Data,” in the Journal of Proteome Research.

The Center for Continuum Computing at PNNL aims to integrate cloud platforms, high-performance computing, and edge devices into a seamless ecosystem that accelerates scientific discovery.

Formal mathematics both reveals what’s inside the black box of AI algorithms and pushes the boundary of what’s possible within math as a discipline.

Federal environmental permitting process to be fast-tracked with AI-powered tools and cloud-supported data analysis.

Calculating quantum chemistry quickly allows scientists to refine their understanding of complex chemical systems.

A team of researchers at PNNL is developing a new approach to explore the higher-dimensional shape of cyber systems to identify signatures of adversarial attacks.

Samrat (Sam) Chatterjee, a PNNL chief data scientist and team leader with the Data Sciences and Machine Intelligence group, was co-author of a CSET workshop report on agentic artificial intellilligence

PNNL computational and data scientist Mark Maupin was the team lead for a paper published in the journal Molecules.

Researchers discussed this topic at the 2024 Analog Computing for Science Workshop co-led by Antonino Tumeo.

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

With her broad experience and background, Starr Abdelhadi was selected from many applicants to join the Women in IT Networking at SC (WINS) program for Super Computing 2024 (SC24).

PNNL’s Andrew Engel, Tony Chiang, and Sutanay Choudhury at the 2024 ICLR in Vienna.

Samantha Erwin, a PNNL data scientist, was recently appointed to the Society for Industrial and Applied Mathematics Membership Committee.

Pacific Northwest National Laboratory launches the Training Outreach and Recruitment for Cybersecurity Hydropower program at the University of Texas at El Paso.

Brett Jefferson, data scientist, was recently recognized for his determination and success in his research space with an Early Career Award from Indiana University Bloomington in the Psychological and Brain Sciences Department.

Spatial proteomics enables researchers to link protein measurements to features in the image of a tissue sample, which are lost using standard approaches.

PNNL has created the Center for AI @PNNL to coordinate the pioneering research of hundreds of scientists working on a range of projects in artificial intelligence.

Input from humans helps when deciding whether to trust the recommendations or decisions of a machine-learning system.

The use of disciplines in pure mathematics can increase the reliability and explainability of machine learning models that “transcend human intuition,” according to PNNL scientists.

Developed with community input, the new Hydropower Vision Roadmap lays out a path to achieve a shared vison for modern hydropower by 2050.