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Researcher
- Ali Passian
- Venkatakrishnan Singanallur Vaidyanathan
- Amir K Ziabari
- Diana E Hun
- Philip Bingham
- Philip Boudreaux
- Ryan Dehoff
- Stephen M Killough
- Vincent Paquit
- Bryan Maldonado Puente
- Charlie Cook
- Christopher Hershey
- Claire Marvinney
- Corey Cooke
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- Daniel Rasmussen
- Gina Accawi
- Gurneesh Jatana
- Harper Jordan
- James Klett
- Joel Asiamah
- Joel Dawson
- John Lindahl
- Mark M Root
- Michael Kirka
- Nance Ericson
- Nolan Hayes
- Obaid Rahman
- Peter Wang
- Ryan Kerekes
- Sally Ghanem
- Srikanth Yoginath
- Tony Beard
- Varisara Tansakul

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

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

The technologies provide a system and method of needling of veiled AS4 fabric tape.

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

Technologies directed quantum spectroscopy and imaging with Raman and surface-enhanced Raman scattering are described.

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).