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Researcher
- Alex Plotkowski
- Amit Shyam
- Ryan Dehoff
- Singanallur Venkatakrishnan
- Srikanth Yoginath
- Amir K Ziabari
- Diana E Hun
- James A Haynes
- James J Nutaro
- Philip Bingham
- Philip Boudreaux
- Pratishtha Shukla
- Stephen M Killough
- Sudip Seal
- Sumit Bahl
- Vincent Paquit
- Alice Perrin
- Ali Passian
- Andres Marquez Rossy
- Bryan Maldonado Puente
- Corey Cooke
- Gerry Knapp
- Gina Accawi
- Gurneesh Jatana
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- Joel Asiamah
- Joel Dawson
- Jovid Rakhmonov
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- Nicholas Richter
- Nolan Hayes
- Obaid Rahman
- Pablo Moriano Salazar
- Peeyush Nandwana
- Peter Wang
- Ryan Kerekes
- Sally Ghanem
- Sunyong Kwon
- Varisara Tansakul
- Ying Yang

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

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.

Digital twins (DTs) have emerged as essential tools for monitoring, predicting, and optimizing physical systems by using real-time data.

Simulation cloning is a technique in which dynamically cloned simulations’ state spaces differ from their parent simulation due to intervening events.

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

Current technology for heating, ventilation, and air conditioning (HVAC) and other uses such as vending machines rely on refrigerants that have high global warming potential (GWP).