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Media Contacts
![Julie Smith Julie Smith](/sites/default/files/styles/list_page_thumbnail/public/julie_smith_bb.png?itok=Z9DoY2ss)
It may take a village to raise a child, according to the old proverb, but it takes an entire team of highly trained scientists and engineers to install and operate a state-of-the-art, exceptionally complex ion microprobe. Just ask Julie Smith, a nuclear security scientist at the Depa...
![Default image of ORNL entry sign](/sites/default/files/styles/list_page_thumbnail/public/2023-09/default-thumbnail.jpg?h=553c93cc&itok=N_Kd1DVR)
James Peery, who led critical national security programs at Sandia National Laboratories and held multiple leadership positions at Los Alamos National Laboratory before arriving at the Department of Energy’s Oak Ridge National Laboratory last year, has been named a...
![ORNL Director Thomas Zacharia (center, seated) visited Robertsville Middle School to present a check in support of the school’s CubeSat efforts. ORNL Director Thomas Zacharia (center, seated) visited Robertsville Middle School to present a check in support of the school’s CubeSat efforts.](/sites/default/files/styles/list_page_thumbnail/public/01%202018-P00870%20r1.jpg?itok=lkbKKjXR)
Last November a team of students and educators from Robertsville Middle School in Oak Ridge and scientists from Oak Ridge National Laboratory submitted a proposal to NASA for their Cube Satellite Launch Initiative in hopes of sending a student-designed nanosatellite named RamSat into...
![Germina Ilas (left) and Ian Gauld review spent fuel data entries in the SFCOMPO 2.0 database. Germina Ilas (left) and Ian Gauld review spent fuel data entries in the SFCOMPO 2.0 database.](/sites/default/files/styles/list_page_thumbnail/public/news/images/2018-P00005_r3_0.jpg?itok=FrGhhOuK)
![ORNL’s Steven Young (left) and Travis Johnston used Titan to prove the design and training of deep learning networks could be greatly accelerated with a capable computing system. ORNL’s Steven Young (left) and Travis Johnston used Titan to prove the design and training of deep learning networks could be greatly accelerated with a capable computing system.](/sites/default/files/styles/list_page_thumbnail/public/news/images/RAvENNA%20release%20pic.png?itok=2bDpK5Mo)
A team of researchers from the Department of Energy’s Oak Ridge National Laboratory has married artificial intelligence and high-performance computing to achieve a peak speed of 20 petaflops in the generation and training of deep learning networks on the