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.
The eighth Arab-American Frontiers of Science, Engineering, and Medicine Symposium, co-organized by PNNL engineer and research line manager Leonard Pease, brought together multi-disciplinary researchers from around the globe.
Sam Rosenberg, a data research scientist in the Energy and Environment Directorate at PNNL, has been appointed voting member of the Regional Technical Forum for the Northwest Power Conservation Council.
Steven Spurgeon, a materials scientist and microscopy researcher at PNNL, has accepted an affiliate associate professorship at the University of Washington Department of Physics.
Williams brings his deep understanding of the technology industry and PNNL’s quantum and national security expertise to this Technical Advisory Committee.
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 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.
Royer’s research has focused on ensuring that energy efficient lighting technologies, like LEDs, offer quality light so they reach their potential for energy savings.
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.
The U.S. Department of Energy has selected the Scalable Predictive Methods for Excitations and Correlated Phenomena project to receive funding to develop software for chemical research.