Savannah River National Laboratory showcased how it’s advancing the U.S. Department of Energy’s Genesis Mission through applied artificial intelligence and machine learning research and innovation at the 2026 AI+ Expo in Washington, D.C. May 19, 2026
Office of Environmental Management
May 19, 2026Tom Danielson with Savannah River National Laboratory discusses how artificial intelligence can accelerate nuclear cleanup solutions, turning waste into useable materials such as glass and grout.
WASHINGTON, D.C. — Savannah River National Laboratory (SRNL) showcased how it’s advancing the U.S. Department of Energy’s (DOE) Genesis Mission through applied artificial intelligence (AI) and machine learning research and innovation at the 2026 AI+ Expo in Washington, D.C.
Energy Secretary Chris Wright opened the event with a fireside chat, then dropped by the DOE Pavilion in the exhibition hall, drawing a crowd to the booth who heard SRNL’s Tom Danielson give the first Genesis Mission project presentation of the day. This helped establish SRNL’s strong participation in an initiative that DOE has deemed a top priority.
The Savannah River National Laboratory was one of the 17 national laboratories to represent the U.S. Department of Energy (DOE) at the 2026 AI+ Expo in Washington, D.C. At the DOE Pavilion, officials emphasized the value of the national laboratories in applying the power of artificial intelligence and advancing science through the Genesis Mission.
Later, SRNL researchers Zachary Tener and Vincent DiNova continued the momentum with their AI-focused demonstrations that highlighted SRNL’s leadership in critical materials recovery and AI-enabled manufacturing. SRNL is the DOE’s Office of Environmental Management sole-sponsored laboratory.
SRNL broadened its impact through engagements with national lab computing leadership and an impromptu conversation with DOE Under Secretary for Science Darío Gil, who leads the Genesis Mission.
SRNL’s presence reinforced the lab’s integral role in delivering mission-driven AI capabilities across the 17 DOE national laboratories.
Read more about SRNL’s AI and machine learning efforts in the latest edition of Matter Magazine.
-Contributor: Sara Shoemaker
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