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As a data scientist, Daniel Adams uses storytelling to parse through a large amount of information to determine which elements are most important, paring down the data to result in the most efficient and accurate data set possible.

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Despite strong regulations and robust international safeguards, authorities routinely interdict nuclear materials outside of regulatory control. Researchers at ORNL are exploring a new method that would give authorities the ability to analyze intercepted nuclear material and determine where it originated. 

Caption: Participants gather for a group photo after discussing securing AI systems for critical national security data and applications.  Photo by Liz Neunsinger/ORNL, U.S. Dept. of Energy

Researchers at the Department of Energy’s Oak Ridge National Laboratory met recently at an AI Summit to better understand threats surrounding artificial intelligence. The event was part of ORNL’s mission to shape the future of safe and secure AI systems charged with our nation’s most precious data. 

Mohamad Zineddin

Mohamad Zineddin hopes to establish an interdisciplinary center of excellence for nuclear security at ORNL, combining critical infrastructure assessment and protection, risk mitigation, leadership in nuclear security, education and training, nuclear security culture and resilience strategies and techniques.

Joon-Seok Kim Credit: Genevieve Martin/ORNL, U.S. Dept. of Energy

Researchers at ORNL are using a machine-learning model to answer ‘what if’ questions stemming from major events that impact large numbers of people. By simulating an event, such as extreme weather, researchers can see how people might respond to adverse situations, and those outcomes can be used to improve emergency planning.

Quietly making noise: Measuring differential privacy could balance meaningful analytics and identity protection

To balance personal safety and research innovation, researchers at ORNL are employing a mathematical technique known as differential privacy to provide data privacy guarantees.

The EPA approved the registration and use of a renewable gasoline blendstock developed by Vertimass LLC and Oak Ridge National Laboratory that can significantly reduce vehicle emissions when added to conventional fuels. Credit: Adam Malin/ORNL, U.S. Dept. of Energy

The U.S. Environmental Protection Agency has approved the registration and use of a renewable gasoline blendstock developed by Vertimass LLC and ORNL that can significantly reduce the emissions profile of vehicles when added to conventional fuels.

ORNL researchers to present wireless charging technology in OTT’s Discovery Series webinar

ORNL’s Omer Onar and Mostak Mohammad will present on ORNL's wireless charging technology in DOE’s Office of Technology Transitions National Lab Discovery Series Tuesday, April 30. 

 

 

DOE national laboratory scientists led by Oak Ridge National Laboratory have developed the first tree dataset of its kind, bridging molecular information about the poplar tree microbiome to ecosystem-level processes. Credit: Andy Sproles, ORNL/U.S. Dept. of Energy

A first-ever dataset bridging molecular information about the poplar tree microbiome to ecosystem-level processes has been released by a team of DOE scientists led by ORNL. The project aims to inform research regarding how natural systems function, their vulnerability to a changing climate and ultimately how plants might be engineered for better performance as sources of bioenergy and natural carbon storage.

ORNL researchers are developing algorithms and multilayered communication and control systems that make electric vehicle chargers operate more reliably, even if there is a voltage drop or disturbance in the electric grid. Credit: Andy Sproles/ORNL, US Dept. of Energy

ORNL researchers are working to make EV charging more resilient by developing algorithms to deal with both internal and external triggers of charger failure. This will help charging stations remain available to traveling EV drivers, reducing range anxiety.