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Media Contacts
![ORNL researchers are establishing a digital thread of data, algorithms and workflows to produce a continuously updated model of earth systems.](/sites/default/files/styles/list_page_thumbnail/public/2023-11/MicrosoftTeams-image%20%2823%29_0.png?h=c6980913&itok=cK99Pg3y)
Digital twins are exactly what they sound like: virtual models of physical reality that continuously update to reflect changes in the real world.
![Director of ORNL’s AI Initiative Prasanna Balaprakash addresses attendees at the Generative AI for ORNL Science Workshop. Credit: ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2023-09/prasannaSMC2023_0.jpg?h=89f9a9b4&itok=N5nInOPo)
The Department of Energy’s Oak Ridge National Laboratory hosted its Smoky Mountains Computational Science and Engineering Conference for the first time in person since the COVID pandemic broke in 2020. The conference, which celebrated its 20th consecutive year, took place at the Crowne Plaza Hotel in downtown Knoxville, Tenn., in late August.
![Sophie Voisin, an ORNL software engineer, was part of a team that won a 2014 R&D 100 Award for work on Intelligent Software for a Personalized Modeling of Expert Opinions, Decisions and Errors in Visual Examination Tasks. Credit: Jason Richards/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2022-08/algo-crop2.jpg?h=384d27f0&itok=qfe3b2Fx)
Cameras see the world differently than humans. Resolution, equipment, lighting, distance and atmospheric conditions can impact how a person interprets objects on a photo.
![Data from different sources are joined on platforms created by ORNL researchers to offer better information for decision makers. Credit: ORNL/Nathan Armistead](/sites/default/files/styles/list_page_thumbnail/public/2022-07/COVID%20dashboards%20story%20graphic_0.jpg?h=d1cb525d&itok=ubNOO2W4)
When the COVID-19 pandemic stunned the world in 2020, researchers at ORNL wondered how they could extend their support and help
![ORNL scientists created a geodemographic cluster for the Atlanta metro area that identifies risk factors related to climate impacts. Credit: ORNL/U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2022-06/climateMapCorrection_0.jpg?h=5c1b3784&itok=ijIvJETa)
Scientists develop environmental justice lens to identify neighborhoods vulnerable to climate change
A new capability to identify urban neighborhoods, down to the block and building level, that are most vulnerable to climate change could help ensure that mitigation and resilience programs reach the people who need them the most.
![LandScan Global depicts population distribution estimates across the planet. The darker orange and red colors above indicate higher population density. Credit: ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2022-05/Picture1_0.jpg?h=9d172ced&itok=uYwYp-pW)
It’s a simple premise: To truly improve the health, safety, and security of human beings, you must first understand where those individuals are.
![ORNL, VA and Harvard researchers developed a sparse matrix full of anonymized information on what is thought to be the largest cohort of healthcare data used for this type of research in the U.S. The matrix can be probed with different methods, such as KESER, to gain new insights into human health. Credit: Nathan Armistead/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2022-04/2022-G00330_KESER%20Illustration_0.jpg?h=1cb48fc4&itok=c6ZuDdDg)
A team of researchers has developed a novel, machine learning–based technique to explore and identify relationships among medical concepts using electronic health record data across multiple healthcare providers.
![Earth Day](/sites/default/files/styles/list_page_thumbnail/public/2022-04/Earth%20image.png?h=8f74817f&itok=5rQ_su9Z)
Tackling the climate crisis and achieving an equitable clean energy future are among the biggest challenges of our time.
![An ORNL-led team comprising researchers from multiple DOE national laboratories is using artificial intelligence and computational screening techniques – in combination with experimental validation – to identify and design five promising drug therapy approaches to target the SARS-CoV-2 virus. Credit: Michelle Lehman/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2021-06/frame1.png?h=d1cb525d&itok=51pwBWyP)
An ORNL-led team comprising researchers from multiple DOE national laboratories is using artificial intelligence and computational screening techniques – in combination with experimental validation – to identify and design five promising drug therapy approaches to target the SARS-CoV-2 virus.
![Deborah Frincke, one of the nation’s preeminent computer scientists and cybersecurity experts, serves as associate laboratory director of ORNL’s National Security Science Directorate. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2021-05/Deborah%20Frincke%20profile_0.jpg?h=8caed45b&itok=0eTC4gMH)
Deborah Frincke, one of the nation’s preeminent computer scientists and cybersecurity experts, serves as associate laboratory director of ORNL’s National Security Science Directorate. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy