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Media Contacts
![AI-driven attention mechanisms aid in streamlining cancer pathology reporting.](/sites/default/files/styles/list_page_thumbnail/public/2024-03/attention%20mechanism%20%282%29.jpg?h=3a7a7cb1&itok=_OJowEl4)
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
![Sean Oesch](/sites/default/files/styles/list_page_thumbnail/public/2024-03/Picture1.jpg?h=b6c94d59&itok=HaSGWHLY)
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 Kapadia](/sites/default/files/styles/list_page_thumbnail/public/2024-03/kapadia.jpg?h=8f9cfe54&itok=M4gtR_dd)
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.
![ORNL](/sites/default/files/styles/list_page_thumbnail/public/2024-02/53513409869_10ff1eb2d4_k.jpg?h=a1e1a043&itok=3CjbVfyQ)
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.
![New system combines human, artificial intelligence to improve experimentation](/sites/default/files/styles/list_page_thumbnail/public/2024-02/Screenshot%202024-02-14%20at%2011.37.46%20AM%20%281%29.png?h=e621a1e2&itok=N3lsBqrh)
To capitalize on AI and researcher strengths, scientists developed a human-AI collaboration recommender system for improved experimentation performance.
![A multidirectorate group from ORNL attended AGU23 and came away inspired for the year ahead in geospatial, earth and climate science](/sites/default/files/styles/list_page_thumbnail/public/2024-02/MicrosoftTeams-image%20%2815%29%20%281%29.png?h=a5eb5da0&itok=gY269KaC)
ORNL scientists and researchers attended the annual American Geophysical Union meeting and came away inspired for the year ahead in geospatial, earth and climate science.
![: ORNL climate modeling expertise contributed to an AI-backed model that assesses global emissions of ammonia from croplands now and in a warmer future, while identifying mitigation strategies. This map highlights croplands around the world. Credit: U.S. Geological Survey](/sites/default/files/styles/list_page_thumbnail/public/2024-02/global_croplands_usgs_globe-4g_1.png?h=4016a495&itok=rb8eHyvK)
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.
![Prasad Kandula builds a medium-voltage solid state circuit breaker as part of ORNL’s project to develop medium-voltage power electronics in GRID-C. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2024-01/2023-p19949.jpg?h=036a71b7&itok=hk4ue1hl)
Scientists at ORNL are looking for a happy medium to enable the grid of the future, filling a gap between high and low voltages for power electronics technology that underpins the modern U.S. electric grid.
![Ilenne Del Valle is merging her expertise in synthetic biology and environmental science to develop new technologies to help scientists better understand and engineer ecosystems for climate resilience. Credit: Carlos Jones/ORNL, U.S. Dept of Energy](/sites/default/files/styles/list_page_thumbnail/public/2024-02/2023-p19402.jpg?h=036a71b7&itok=WlSmSAEH)
Ilenne Del Valle is merging her expertise in synthetic biology and environmental science to develop new technologies to help scientists better understand and engineer ecosystems for climate resilience.
![Using a better modeling framework, with data collected from Mississippi Delta marshes, scientists are able to improve the predictions of methane and other greenhouse gas emissions. Credit: Matthew Berens/ORNL, U.S Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2024-01/picture1_0.jpg?itok=uQVJerN0)
Scientists at the Department of Energy’s Oak Ridge National Laboratory are using a new modeling framework in conjunction with data collected from marshes in the Mississippi Delta to improve predictions of climate-warming methane and nitrous oxide.