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Media Contacts
![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.
![Moriano awarded early career fellowship for underrepresented groups](/sites/default/files/styles/list_page_thumbnail/public/2024-02/Pablo-Moriano-Pic.jpg?h=4d38fa4a&itok=QTrNiMK-)
Pablo Moriano, a research scientist in the Computer Science and Mathematics Division at ORNL, was selected as a member of the 2024 Class of MGB-SIAM Early Career Fellows.
![: 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.
![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.
![ORNL Associate Laboratory Director for Computing and Computational Sciences. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2024-01/tourassi.jpg?h=55be468c&itok=AvEfpuPK)
Gina Tourassi, associate laboratory director for computing and computational sciences at the US Department of Energy’s (DOE’s) Oak Ridge National Laboratory, has been named a fellow of the Institute of Electrical and Electronics Engineers, the world’s largest organization for technical professionals.
![Applications for the U.S. Quantum Information Science Summer School are open until March 15, 2024. Credit: Laddy Fields/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2024-01/qscsummerschool.jpg?h=d1cb525d&itok=1RYUfoME)
From July 15 to 26, 2024, the Department of Energy’s Oak Ridge National Laboratory will host the second U.S. Quantum Information Science, or QIS, Summer School.
![Conversion of an atomic structure into a graph, where atoms are treating as nodes and interatomic bonds as edges. Credit: Massimiliano “Max” Lupo Pasini/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2024-01/hydra_gnn_diagram.png?h=2deb2cea&itok=4OvY68cs)
Researchers at the Department of Energy’s Oak Ridge and Lawrence Berkeley National Laboratories are evolving graph neural networks to scale on the nation’s most powerful computational resources, a necessary step in tackling today’s data-centric
![ORNL’s Tomás Rush examines a culture as part of his research into the plant-fungus relationship that can help or hinder ecosystem health. Credit: Genevieve Martin/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2024-01/2022-p09834_0.jpg?h=c6980913&itok=iHPtg7RM)
New computational framework speeds discovery of fungal metabolites, key to plant health and used in drug therapies and for other uses.