PNNL will play a key role in advancing Connected Communities made up of efficient homes and buildings that communicate with the grid to produce energy and environmental benefits.

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

PNNL researchers developed a way to produce accurate simulations of complex physical systems using renormalized approximations across multiple scales

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

A new model offers more accurate predictions of how intensely hurricanes may strike.

PNNL data scientists are refining their artificial intelligence tools with COVID-19 data to advance therapeutics and treatments for a future pandemic.

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 virologist Amy Sims’s coronavirus research paper was among 50 most-downloaded articles related to SARS-CoV-2 in 2020.

Scientists created a benchmark dataset and explored new algorithms to better predict changes in the intensity of North Atlantic tropical cyclones.

Researchers at PNNL examined heat pump water heater (HPWH) operation in Pacific Northwest residences, gaining insights into HPWH electricity use patterns. Part of the study captured trends during a COVID-19 stay-at-home order.

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

Slaven Peles, PNNL computational scientist and leader of a national high-performance computing project for power grid analysis, spoke about the project with the host of the Let’s Talk Exascale podcast.

Hypergraphs can more faithfully identify important genes in complex immune responses.

PNNL’s Karol Kowalski leads one of the 29 projects selected to receive a total of $73 million in funding.

A team of PNNL researchers are looking at how to evaluate robustness and accountability, fairness, and transparency of artificial intelligence models used to detect and quantify deceptive content online.

A Q&A with Lauren Charles, veterinarian and PNNL data scientist, on zoonotic diseases and the role biosurveillance plays in mitigating the growing threat to global health.

More than 30 PNNL interns contributed to the Airport Risk Assessment Model, a web-based tool that helps airport security stakeholders prioritize resource allocations.

The web-based tool, called PLATIPUS, is publicly available and interacts with publications available in the CovidScholar database.

PNNL’s data-infused approach to electron microscopes’ use in scientific experimentation will help researchers and industry interpret large data streams and drive down costs.