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Media Contacts
![Shift Thermal co-founders Mitchell Ishamel, left, and Levon Atoyan stand in front of one of the company’s ice thermal energy storage modules, which will be submitted to independent measurement and validation testing in May. Credit: Genevieve Martin/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2024-04/shift1.jpg?h=10d202d3&itok=a-cyO6Ev)
Shift Thermal, a member of Innovation Crossroads’ first cohort of fellows, is commercializing advanced ice thermal energy storage for HVAC, shifting the cooling process to be more sustainable, cost-effective and resilient. Shift Thermal wants to enable a lower-cost, more-efficient thermal energy storage method to provide long-duration resilient cooling when the electric grid is down.
![map](/sites/default/files/styles/list_page_thumbnail/public/2024-04/Lab%20Match%20Map.jpg?h=56bf8be4&itok=slCZ2raX)
Three ORNL intellectual property projects with industry partners have advanced in DOE's Office of Technology Transitions Making Advanced Technology Commercialization Harmonized, or Lab MATCH, prize, which encourages entrepreneurs to find actionable pathways that bring lab-developed intellectual property to market.
![ORNL’s Suhas Sreehari explains the algebraic and topological foundations of representation systems, used in generative AI technology such as large language models. Credit: Lena Shoemaker/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2024-04/powered%20by%20match.jpg?h=384e2afb&itok=wJegcDZm)
In the age of easy access to generative AI software, user can take steps to stay safe. Suhas Sreehari, an applied mathematician, identifies misconceptions of generative AI that could lead to unintentionally bad outcomes for a user.
![Credit: Tyler Spano/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2024-04/liz.jpg?h=ab2675cd&itok=jVO3_Ggr)
Nuclear nonproliferation scientists at ORNL have published the Compendium of Uranium Raman and Infrared Experimental Spectra, a public database and analysis of structure-spectral relationships for uranium minerals. This first-of-its-kind dataset and corresponding analysis fill a key gap in the existing body of knowledge for mineralogists and actinide scientists.
![Assaf Anyamba Credit: Carlos Jones/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2024-03/Picture1_1.jpg?h=9fc2b970&itok=XpCeMTbY)
ORNL’s Assaf Anyamba has spent his career using satellite images to determine where extreme weather may lead to vector-borne disease outbreaks. His work has helped the U.S. government better prepare for outbreaks that happen during periods of extended weather events such as El Niño and La Niña, climate patterns in the Pacific Ocean that can affect weather worldwide.
![ORNL](/sites/default/files/styles/list_page_thumbnail/public/2024-03/53513409869_10ff1eb2d4_k.jpg?h=a1e1a043&itok=xpHwXzyO)
ORNL took home the top honors in three categories at the second annual DOE Geospatial Science Poster competition, held on National GIS Day. For the second year in a row, DOE awarded ORNL top prize as Best Geospatial Program. Additionally, ORNL geospatial researchers took home first place prizes for their posters in the Best Departmental Element Alignment and Best Cartography categories.
![ORNL researchers developed a long-sequenced AI transformer capable of processing millions of pathology reports to provide experts researching cancer diagnoses and management with more accurate information on cancer reporting.](/sites/default/files/styles/list_page_thumbnail/public/2024-03/bigbird%20image.jpg?h=8f74817f&itok=VXR7SQWV)
In partnership with the National Cancer Institute, researchers from ORNL and Louisiana State University developed a long-sequenced AI transformer capable of processing millions of pathology reports to provide experts researching cancer diagnoses and management with exponentially more accurate information on cancer reporting.
![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.
![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
![Fengqi “Frank” Li brings computational and architectural expertise to building energy modeling in ORNL’s Grid Interactive Controls group. Genevieve Martin/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2024-02/2023-P18998.jpg?h=036a71b7&itok=ebHvD0wy)
Although he built his career around buildings, Fengqi “Frank” Li likes to break down walls. Li was trained as an architect, but he doesn’t box himself in. Currently he is working as a computational developer at ORNL. But Li considers himself a designer. To him, that’s less a box than a plane – a landscape scattered with ideas, like destinations on a map that can be connected in different ways.