Two different teams that included Oak Ridge National Laboratory employees were honored Feb. 20 with Secretary’s Honor Achievement Awards from the Department of Energy. This is DOE's highest form of employee recognition.
Pablo Moriano, a research scientist in the Computer Science and Mathematics Division at ORNL, was selected as a member of the 2024 Class of MGB-SIAM Early Career Fellows.
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.
Louise Stevenson uses her expertise as an environmental toxicologist to evaluate the effects of stressors such as chemicals and other contaminants on aquatic systems.
A team from DOE’s Oak Ridge, Los Alamos and Sandia National Laboratories has developed a new solver algorithm that reduces the total run time of the Model for Prediction Across Scales-Ocean, or MPAS-Ocean, E3SM’s ocean circulation model, by 45%.
Alex May is the first and only full-time data curator at the Department of Energy’s Oak Ridge Leadership Computing Facility, evaluating datasets developed by computational scientists before they are made public through the OLCF’s Constellation portal for open data exchange.
“Three-Dimensional Breast Cancer Spheroids” submitted by radiotherapeutics researcher Debjani Pal is stunning. Brilliant blue dots pop from an electric sphere threaded with bright colors: greens, aqua, hot pink and red.
Effective Dec. 4, Gina Tourassi will assume responsibilities as associate laboratory director for the Computing and Computational Sciences Directorate at the Department of Energy’s Oak Ridge National Laboratory.
ORNL is home to the world's fastest exascale supercomputer, Frontier, which was built in part to facilitate energy-efficient and scalable AI-based algorithms and simulations.
ORNL has joined a global consortium of scientists from federal laboratories, research institutes, academia and industry to address the challenges of building large-scale artificial intelligence systems and advancing trustworthy and reliable AI for