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Media Contacts
![ORNL identity science researcher Nell Barber works on a facial recognition camera. Credit: Genevieve Martin/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2022-07/Picture1.jpg?h=47322e82&itok=CTajZTiF)
Though Nell Barber wasn’t sure what her future held after graduating with a bachelor’s degree in psychology, she now uses her interest in human behavior to design systems that leverage machine learning algorithms to identify faces in a crowd.
![MDF Exterior](/sites/default/files/styles/list_page_thumbnail/public/2022-06/2021-p07609.jpg?h=be3e4b3a&itok=YfKK7Wy2)
ORNL scientists will present new technologies available for licensing during the annual Technology Innovation Showcase. The event is 9 a.m. to 3 p.m. Thursday, June 16, at the Manufacturing Demonstration Facility at ORNL’s Hardin Valley campus.
![Logan Sturm, Alvin M. Weinberg Fellow at ORNL, creates a mashup between additive manufacturing and cybersecurity research. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2022-05/sturm-lab.jpg?h=1de2f7a8&itok=nYiuVTGx)
How an Alvin M. Weinberg Fellow is increasing security for critical infrastructure components
![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.
![ORNL research scientist Christa Brelsford explained a mathematical framework she developed in 2018, which showed increased availability of infrastructure didn’t necessarily reduce inequality in its access. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2022-04/image001.jpg?h=1579b22a&itok=XzIna_Uc)
Unequal access to modern infrastructure is a feature of growing cities, according to a study published this week in the Proceedings of the National Academy of Sciences
![ORNL scientists created a new microbial trait mapping process that improves on classical protoplast fusion techniques to identify the genes that trigger desirable genetic traits like improved biomass processing. Credit: Nathan Armistead/ORNL, U.S. Dept. of Energy. Reprinted with the permission of Oxford University Press, publisher of Nucleic Acids Research](/sites/default/files/styles/list_page_thumbnail/public/2022-04/Nucleic%20Cover%20Illustration.jpg?h=4a9d1e17&itok=iw81emAt)
ORNL scientists had a problem mapping the genomes of bacteria to better understand the origins of their physical traits and improve their function for bioenergy production.
![Three ORNL scientists have been elected fellows of the American Association for the Advancement of Science, or AAAS, the world’s largest general scientific society and publisher of the Science family of journals. Credit: ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2022-01/AAAS_fellows_resize_0.jpg?h=e91a75a9&itok=y20mbH61)
Three ORNL scientists have been elected fellows of the American Association for the Advancement of Science, or AAAS, the world’s largest general scientific society and publisher of the Science family of journals.
![Watermarks, considered the most efficient mechanisms for tracking how complete streaming data processing is, allow new tasks to be processed immediately after prior tasks are completed. Image Credit: Nathan Armistead, ORNL](/sites/default/files/styles/list_page_thumbnail/public/2021-11/Watermarks%5B1%5D.jpg?h=f7cc716d&itok=Er5k0WwK)
A team of collaborators from ORNL, Google Inc., Snowflake Inc. and Ververica GmbH has tested a computing concept that could help speed up real-time processing of data that stream on mobile and other electronic devices.