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Media Contacts
Kate Evans, director for the Computational Sciences and Engineering Division at ORNL, has been awarded the 2024 Society for Industrial and Applied Mathematicians Activity Group on Mathematics of Planet Earth Prize.
A team of researchers at ORNL demonstrated that a light-duty passenger electric vehicle can be wirelessly charged at 100-kW with 96% efficiency using polyphase electromagnetic coupling coils with rotating magnetic fields.
In partnership with the National Cancer Institute, researchers from the Department of Energy’s Oak Ridge National Laboratory’s Modeling Outcomes for Surveillance using Scalable Artificial Intelligence are building on their groundbreaking work to
While government regulations are slowly coming, a group of cybersecurity professionals are sharing best practices to protect large language models powering these tools. Sean Oesch, a leader in emerging cyber technologies, recently contributed to the OWASP AI Security and Privacy Guide to inform global AI security standards and regulations.
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.
Since 2019, a team of NASA scientists and their partners have been using NASA’s FUN3D software on supercomputers located at the Department of Energy’s Oak Ridge Leadership Computing Facility to conduct computational fluid dynamics simulations of a human-scale Mars lander. The team’s ongoing research project is a first step in determining how to safely land a vehicle with humans onboard onto the surface of Mars.
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.
To capitalize on AI and researcher strengths, scientists developed a human-AI collaboration recommender system for improved experimentation performance.
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.
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.