ORNL took home the top honors in three categories at the second annual DOE Geospatial Science Poster competition, held on National GIS Day. For the second year in a row, DOE awarded ORNL top prize as Best Geospatial Program. Additionally, ORNL geospatial researchers took home first place prizes for their posters in the Best Departmental Element Alignment and Best Cartography categories.
Anuj J. Kapadia, who heads the Advanced Computing Methods for Health Sciences Section at ORNL, has been elected as president of the Southeastern Chapter of the American Association of Physicists in Medicine.
Lieutenant Commander Rich Harvey has spent the last three decades of his career serving his country. Harvey's efforts supporting the Office of Naval Research has earned him the 2023 Junior Scientist Officer of the Year award for coordination and computer modeling support for a project called TALISMAN, his leadership roles and other exemplary service markers.
To capitalize on AI and researcher strengths, scientists developed a human-AI collaboration recommender system for improved experimentation performance.
ORNL climate modeling expertise contributed to a project that assessed global emissions of ammonia from croplands now and in a warmer future, while also identifying solutions tuned to local growing conditions.
Gina Tourassi, associate laboratory director for computing and computational sciences at the US Department of Energy’s (DOE’s) Oak Ridge National Laboratory, has been named a fellow of the Institute of Electrical and Electronics Engineers, the world’s largest organization for technical professionals.
Technologies developed by researchers at ORNL have received six 2023 R&D 100 Awards.
Oak Ridge National Laboratory scientists exploring bioenergy plant genetics have made a surprising discovery: a protein domain that could lead to new COVID-19 treatments.
ORNL researchers discovered genetic mutations that underlie autism using a new approach that could lead to better diagnostics and drug therapies.
Researchers from ORNL, the University of Tennessee at Chattanooga and Tuskegee University used mathematics to predict which areas of the SARS-CoV-2 spike protein are most likely to mutate.