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Media Contacts
![Frontier supercomputer](/sites/default/files/styles/list_page_thumbnail/public/2023-06/Frontier-logos_0.jpg?h=c6980913&itok=yuF5A0wj)
Innovations in artificial intelligence are rapidly shaping our world, from virtual assistants and chatbots to self-driving cars and automated manufacturing.
![ORNL seismic researcher Chengping Chai placed seismic sensors on the ground at various distances from an ORNL nuclear reactor to learn whether they could detect its operating state. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2023-06/2023-P03398.jpg?h=3e43625b&itok=TXK8tthh)
Like most scientists, Chengping Chai is not content with the surface of things: He wants to probe beyond to learn what’s really going on. But in his case, he is literally building a map of the world beneath, using seismic and acoustic data that reveal when and where the earth moves.
![ORNL researchers, from left, Yang Liu, Xiaohan Yang and Torik Islam, collaborated on the development of a new capability to insert multiple genes simultaneously for fast, efficient transformation of plants into better bioenergy feedstocks. Credit: Genevieve Martin/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2023-06/Gene%20stacking%202023-P03111_0.jpg?h=c6980913&itok=RSUZXZ8U)
In a discovery aimed at accelerating the development of process-advantaged crops for jet biofuels, scientists at ORNL developed a capability to insert multiple genes into plants in a single step.
![ORNL’s Debangshu Mukherjee was named an npj Computational Materials “Reviewer of the Year.”](/sites/default/files/styles/list_page_thumbnail/public/2023-05/IMG.png?h=4af88f53&itok=uXshKvMk)
ORNL’s Debangshu Mukherjee has been named an npj Computational Materials “Reviewer of the Year.”
![Matt Sieger. Credit: Carlos Jones/ORNL](/sites/default/files/styles/list_page_thumbnail/public/2023-05/2022-P00437_0.jpg?h=c6980913&itok=bGz_GUB0)
The Oak Ridge Leadership Computing Facility’s Matt Sieger has been named the project director for the OLCF-6 effort. This next OLCF undertaking will plan and build a world-class successor to the OLCF’s still-new exascale system, Frontier.
![ORNL’s Shih-Chieh Kao has been named a 2023 fellow of the American Society of Civil Engineers’ Environmental & Water Resources Institute. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2023-05/Kao%202015-P06127_0.jpg?h=49ab6177&itok=5Qm0lUjE)
Shih-Chieh Kao, manager of the Water Power program at ORNL, has been named a fellow of the American Society of Civil Engineer’s Environmental & Water Resources Institute, or EWRI.
![Colleen Iversen is the new director of NGEE Arctic, leading a large cross-disciplinary team of scientists in pursuit of a better understanding of Arctic climate processes. Credit: ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2023-05/Colleen_crop1.png?h=707772c7&itok=9f3Cyi_G)
Colleen Iversen, ecosystem ecologist, group leader and distinguished staff scientist, has been named director of the Next-Generation Ecosystem Experiments Arctic, or NGEE Arctic, a multi-institutional project studying permafrost thaw and other climate-related processes in Alaska.
![ytterbium](/sites/default/files/styles/list_page_thumbnail/public/2023-05/Ytterbium-176%20approved%20crop_0.jpg?h=1f8bb2ae&itok=lTsZ7UjW)
ORNL’s electromagnetic isotope separator, or EMIS, made history in 2018 when it produced 500 milligrams of the rare isotope ruthenium-96, unavailable anywhere else in the world.
![Computing pioneer Jack Dongarra has been elected to the National Academy of Sciences.](/sites/default/files/styles/list_page_thumbnail/public/2023-05/Dongarra%20thumbnail.png?h=560fc75e&itok=ByoO7Sli)
Computing pioneer Jack Dongarra has been elected to the National Academy of Sciences in recognition of his distinguished and continuing achievements in original research.
![An AI-generated image representing atoms and artificial neural networks. Credit: Maxim Ziatdinov, ORNL](/sites/default/files/styles/list_page_thumbnail/public/2023-04/atoms3.jpg?h=ab622562&itok=dNMzrFw8)
Researchers at ORNL have developed a machine-learning inspired software package that provides end-to-end image analysis of electron and scanning probe microscopy images.