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Bryan Maldonado

As a mechanical engineer in building envelope materials research at ORNL, Bryan Maldonado sees opportunities to apply his scientific expertise virtually everywhere he goes, from coast to coast. As an expert in understanding how complex systems operate, he’s using machine learning methods to control the process and ultimately optimize performance. 

ORNL researchers demonstrated the use of drones equipped with cameras and other sensors to check power lines at an EPB of Chattanooga training center for electrical line workers.

Researchers at ORNL recently demonstrated an automated drone-inspection technology at EPB of Chattanooga that will allow utilities to more quickly and easily check remote power lines for malfunctions, catching problems before outages occur.

Debjani Singh

Debjani Singh, a senior scientist at ORNL, leads the HydroSource project, which enhances hydropower research by making water data more accessible and useful. With a background in water resources, data science, and earth science, Singh applies innovative tools like AI to advance research. Her career, shaped by her early exposure to science in India, focuses on bridging research with practical applications.

This photo is of a male scientist sitting at a desk working with materials, wearing protective glasses.

Researchers at the Department of Energy’s Oak Ridge National Laboratory and partner institutions have launched a project to develop an innovative suite of tools that will employ machine learning algorithms for more effective cybersecurity analysis of the U.S. power grid. 

ORNL researchers Phani Marthi and Suman Debnath work on developing and scaling up new EMT simulation software to analyze how power electronics in the electric grid will respond to brief interruptions in power flow. Credit: Genevieve Martin/ORNL, U.S. Dept. of Energy

Power companies and electric grid developers turn to simulation tools as they attempt to understand how modern equipment will be affected by rapidly unfolding events in a complex grid. 

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Oak Ridge National Laboratory has named Troy A. Carter director of the Fusion Energy Division in ORNL’s Fusion and Fission Energy and Science Directorate, or FFESD. 

A macaroni shaped material in colorful rings, purple, red, blue, red, orange and then black.

A new study conducted on the Frontier supercomputer gave researchers new clues to improving fusion confinement. This research, in collaboration with General Atomics and UC San Diego, uncovered that the interaction between ions and electrons near the tokamak's edge can unexpectedly increase turbulence, challenging previous assumptions about how to optimize plasma confinement for efficient nuclear fusion.

Man in blue shirt and grey pants holds laptop and poses next to a green plant in a lab.

John Lagergren, a staff scientist in Oak Ridge National Laboratory’s Plant Systems Biology group, is using his expertise in applied math and machine learning to develop neural networks to quickly analyze the vast amounts of data on plant traits amassed at ORNL’s Advanced Plant Phenotyping Laboratory.

ORNL researcher Louise Evans is working to ensure safeguards approaches and verification technologies are integrated early in the design process of advanced reactor technologies. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

Researchers tackling national security challenges at ORNL are upholding an 80-year legacy of leadership in all things nuclear. Today, they’re developing the next generation of technologies that will help reduce global nuclear risk and enable safe, secure, peaceful use of nuclear materials, worldwide.

A team led by Oak Ridge National Laboratory researchers used Frontier to explore training strategies for one of the largest artificial intelligence models to date. Credit: Getty Images

A team led by researchers at ORNL explored training strategies for one of the largest artificial intelligence models to date with help from the world’s fastest supercomputer. The findings could help guide training for a new generation of AI models for scientific research.