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Researcher
- Isabelle Snyder
- Alex Plotkowski
- Amit Shyam
- Ryan Dehoff
- Venkatakrishnan Singanallur Vaidyanathan
- Adam Siekmann
- Amir K Ziabari
- Diana E Hun
- Emilio Piesciorovsky
- James A Haynes
- Philip Bingham
- Philip Boudreaux
- Stephen M Killough
- Subho Mukherjee
- Sumit Bahl
- Vincent Paquit
- Vivek Sujan
- Aaron Werth
- Aaron Wilson
- Alice Perrin
- Ali Riza Ekti
- Andres Marquez Rossy
- Bryan Maldonado Puente
- Corey Cooke
- Elizabeth Piersall
- Eve Tsybina
- Gary Hahn
- Gerry Knapp
- Gina Accawi
- Gurneesh Jatana
- John Holliman II
- Jovid Rakhmonov
- Mark M Root
- Michael Kirka
- Nicholas Richter
- Nils Stenvig
- Nolan Hayes
- Obaid Rahman
- Ozgur Alaca
- Peeyush Nandwana
- Peter Wang
- Raymond Borges Hink
- Ryan Kerekes
- Sally Ghanem
- Sunyong Kwon
- Viswadeep Lebakula
- Yarom Polsky
- Ying Yang

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

How fast is a vehicle traveling? For different reasons, this basic question is of interest to other motorists, insurance companies, law enforcement, traffic planners, and security personnel. Solutions to this measurement problem suffer from a number of constraints.

Currently available cast Al alloys are not suitable for various high-performance conductor applications, such as rotor, inverter, windings, busbar, heat exchangers/sinks, etc.

The invented alloys are a new family of Al-Mg alloys. This new family of Al-based alloys demonstrate an excellent ductility (10 ± 2 % elongation) despite the high content of impurities commonly observed in recycled aluminum.

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.

Water heaters and heating, ventilation, and air conditioning (HVAC) systems collectively consume about 58% of home energy use.

This disclosure introduces an innovative tool that capitalizes on historical data concerning the carbon intensity of the grid, distinct to each electric zone.

This disclosure introduces an innovative tool that capitalizes on historical data concerning the carbon intensity of the grid, distinct to each electric zone.

This invention utilizes new techniques in machine learning to accelerate the training of ML-based communication receivers.