Christina Lomasney moderates panel on commercialization pathways for emerging artificial intelligence and high-performance computing technologies.

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.

PNNL’s Center for Cloud Computing is addressing challenges in data management and hybrid cloud solutions with industry and academic partnerships.

PNNL's accomplishments in FY 2024 help address the remaining challenges the wind industry faces.

In a recent publication in Nature Communications, a team of researchers presents a mathematical theory to address the challenge of barren plateaus in quantum machine learning.

PNNL had a significant presence at October’s North American Wind Energy Academy/WindTech 2023 Conference in Denver, Colorado. Thirteen PNNL wind experts participated in various capacities.

Scientists have developed a better way to recognize denial-of-service internet attacks, improving detection by 90 percent.

PNNL researchers outline open problems in different scientific areas in the Journal of Combinatorics.

Researchers have knitted together three large databases of information to help cybersecurity experts detect and prevent attacks.

Scientists have taken a key step toward harnessing a form of AI known as deep reinforcement learning to protect computer networks.

A research buoy managed by PNNL has been deployed in Hawai’ian waters, collecting oceanographic and meteorological measurements off the coast of O’ahu.

Multidisciplinary teams from research and industry are brought together using management systems developed by a team of software engineers at PNNL.

HiSVSIM enables large-scale quantum simulations through graph partitioning.

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

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

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

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

Researchers to design their own computer accelerators for faster analysis of large datasets.

PNNL’s Data Archive and Portal that stores and disseminates wind energy data recently reached a major milestone: 1,000 users and growing.

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