Data scientist Jung Lee accepted the position of review editor for Frontiers in Computational Neuroscience after serving as a guest editor for a special issue.
PNNL mathematician Aaron Luttman contributed to the organizing committee for workshop exploring robust machine learning and artificial intelligence systems for the U.S. Army.
Steven Spurgeon’s research is featured in the cover of the MRS Bulletin along with his team’s invited perspective on the future of machine learning for electron and scanning probe microscopy.
PNNL Chief Scientist for Computing Jim Ang will be part of a DOE Office of Science virtual discussion regarding industry collaborations on AI hardware.
PNNL data scientist to edit collection of research articles focused on understanding how microcircuits function in the brain and in artificial intelligence systems.
A paper co-authored by Courtney Corley was recently selected as the most influential paper for the Twenty-First National Conference on Artificial Intelligence.
Four research staff from PNNL are part of an international team that earned top honors for a journal paper focused on a new algorithm-evaluation approach for buildings.
Anika Halappanavar’s research into COVID-19 misinformation earned her recognition by the Washington State Academy of Sciences as one of the state’s top high school researchers.
Steven Spurgeon, a materials scientist and microscopy researcher at PNNL, has accepted an affiliate associate professorship at the University of Washington Department of Physics.
Human-machine teaming may sound like something from the distant future. In “Human-Machine Teaming: A Vision of Future Law Enforcement” in Domestic Preparedness, Corey Fallon, Kris Cook, and Grant Tietje of PNNL examine this topic.
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.
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.
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.
More than 30 PNNL interns contributed to the Airport Risk Assessment Model, a web-based tool that helps airport security stakeholders prioritize resource allocations.
Svitlana Volkova, chief scientist for decision intelligence and analytics at PNNL, was invited as a panelist at the SIAM International Conference on Data Mining
PNNL computer scientists joined international leaders in machine learning to present research to detect and address potential cybersecurity threats and devise epidemic interventions.
