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- Ryan Dehoff
- Singanallur Venkatakrishnan
- William Carter
- Alex Roschli
- Ali Riza Ekti
- Amir K Ziabari
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- Brian Post
- Chris Masuo
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- Mostak Mohammad
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- Obaid Rahman
- Oluwafemi Oyedeji
- Omer Onar
- Oscar Martinez
- Ozgur Alaca
- Peter L Fuhr
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- Rangasayee Kannan
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- Sam Hollifield
- Sarah Graham
- Soydan Ozcan
- Sudarsanam Babu
- Tyler Smith
- William Peter
- Xianhui Zhao
- Yarom Polsky
- Yukinori Yamamoto

ORNL researchers have developed a deep learning-based approach to rapidly perform high-quality reconstructions from sparse X-ray computed tomography measurements.

This technology can help to increase number of application areas of Wireless Power Transfer systems. It can be applied to consumer electronics, defense industry, automotive industry etc.

We have been working to adapt background oriented schlieren (BOS) imaging to directly visualize building leakage, which is fast and easy.

Faults in the power grid cause many problems that can result in catastrophic failures. Real-time fault detection in the power grid system is crucial to sustain the power systems' reliability, stability, and quality.

The use of biomass fiber reinforcement for polymer composite applications, like those in buildings or automotive, has expanded rapidly due to the low cost, high stiffness, and inherent renewability of these materials. Biomass are commonly disposed of as waste.

Electrical utility substations are wired with intelligent electronic devices (IEDs), such as protective relays, power meters, and communication switches.