Bill Cannon Co-authors Machine Learning Journal Article
Bill Cannon, senior scientist and biophysicist in the Computational Mathematics Group, was a co-author of a recent article published in Nature Partner Journals-Digital Medicine.
Mathematics for Artificial Reasoning in Science
The Mathematics for Artificial Reasoning in Science (MARS) initiative seeks to complement machine learning and deep learning to advance science.
Science for the Front Line: Svitlana Volkova
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.
Mega AI
Mega AI seeks to develop massive-scale, self-supervised, multimodal foundation models of scientific knowledge capable of general-purpose inferences to enable reasoning with existing knowledge and discovery of new knowledge.
Science for the Front Line: Ralph Perko
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.
Crafting Better Beer
Researchers have been investigating if machine learning techniques could be used to help create novel beers.
PNNL Wins R&D 100 Awards
PNNL has received 119 R&D 100 Awards since 1969, when the laboratory began submitting entries in the contest that recognizes top 100 inventions each year.
Lancaster Publishes Book Chapter on Cyberbiosecurity
Mary Lancaster, epidemiologist and data scientist, co-authored a chapter on cyberbiosecurity for the NATO Science for Peace and Security book series.
Keeping America Safe: David Manz
David Manz is a cybersecurity researcher who is working with cyber-physical systems to better protect the critical infrastructure.
PNNL’s Shadow Figment Technology Foils Cyberattacks
Scientists have created a cybersecurity technology that stops hackers from doing damage by feeding them illusory tidbits of success.