The MIT-sponsored competition encourages community approaches to developing new solutions for analyzing graphs and sparse data; PNNL has placed a winner in each year.

Today’s critical infrastructure systems are increasingly vulnerable to attacks that could cripple civil society, according to cybersecurity experts.

Tracking down nefarious users is just one example of work at PNNL’s Center for Advanced Technology Evaluation, a computing proving ground supported by DOE’s Advanced Scientific Computing Research program.

Pacific Northwest National Laboratory researchers used machine learning to explore the largest water clusters database, identifying—with the most accurate neural network—important information about this life-essential molecule.

The American Society for Quality (ASQ) has recognized Laboratory Fellow and Pacific Northwest National Laboratory (PNNL) Statistician Greg Piepel with the William G. Hunter Award.

PNNL team has developed and implemented a generalizable computational framework to study the resilience of the multilayered London Rail Network to the compound threat of intense flooding and a targeted cyberattack.

PNNL quantum computing pioneer Nathan Wiebe contributed to a Google-led quantum computing landmark study published in the journal Science.

Making sure there’s enough electricity at the lowest price is a critical endeavor undertaken daily by electricity market operators. Now, there’s an approach that provides more timely and accurate information to make day-ahead decisions.

PNNL scientists have created a tool called WatchOwl to collect more than 4 million tweets per day related to the COVID-19 pandemic. The tool analyzes tweets related to interventions like social distancing and movement restrictions.

Contributions from researchers across Pacific Northwest National Laboratory (PNNL) were recently recognized in the preliminary findings of a Secretary of Energy Advisory Board (SEAB) report.

Ang Li and Antonino Tumeo will present hardware to balance machine learning workloads at a top computer architecture conference.

Researchers performed controlled laboratory experiments using river sediment to test organic matter thermodynamics as a mechanism of metabolic control in areas where groundwater and surface water mix.

Researchers performed a combined analysis of metabolic and gene co-expression networks to explore how the soil microbiome responds to changes in moisture and nutrient conditions.

Researchers trained deep neural networks to accurately predict microbial interactions captured by fluorescence microscopy.

By studying discrete functional components of the soil microbiome at high resolution, researchers obtained a more complete picture of soil diversity compared to analysis of the entire soil community.

PNNL data scientist Carlos M. Ortiz Marrero has co-edited a volume that highlights work at the intersection of quantum computation and mathematics.

The PNNL chemist is leading a joint effort to study circadian rhythms and the gut microbiome.

Accurate identification of metabolites, and other small chemicals, in biological and environmental samples has historically fallen short when using traditional methods.

A new study is among the first to trace the molecular connections between genetics, the gut microbiome and memory in a mouse model bred to resemble the diversity of the human population.

PNNL quantum algorithm theorist and developer Nathan Wiebe is applying ideas from data science and gaming hacks to quantum computing