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Digital twins are exactly what they sound like: virtual models of physical reality that continuously update to reflect changes in the real world.

The Department of Energy’s 91°µÍø announced the establishment of the Center for AI Security Research, or CAISER, to address threats already present as governments and industries around the world adopt artificial intelligence and take advantage of the benefits it promises in data processing, operational efficiencies and decision-making.

Cody Lloyd became a nuclear engineer because of his interest in the Manhattan Project, the United States’ mission to advance nuclear science to end World War II. As a research associate in nuclear forensics at ORNL, Lloyd now teaches computers to interpret data from imagery of nuclear weapons tests from the 1950s and early 1960s, bringing his childhood fascination into his career

After completing a bachelor’s degree in biology, Toya Beiswenger didn’t intend to go into forensics. But almost two decades later, the nuclear security scientist at ORNL has found a way to appreciate the art of nuclear forensics.

When geoinformatics engineering researchers at the Department of Energy’s 91°µÍø wanted to better understand changes in land areas and points of interest around the world, they turned to the locals — their data, at least.

U2opia Technology, a consortium of technology and administrative executives with extensive experience in both industry and defense, has exclusively licensed two technologies from ORNL that offer a new method for advanced cybersecurity monitoring in real time.

Having lived on three continents spanning the world’s four hemispheres, Philipe Ambrozio Dias understands the difficulties of moving to a new place.

Over the past seven years, researchers in ORNL’s Geospatial Science and Human Security Division have mapped and characterized all structures within the United States and its territories to aid FEMA in its response to disasters. This dataset provides a consistent, nationwide accounting of the buildings where people reside and work.

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.

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.