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Researcher
- Venkatakrishnan Singanallur Vaidyanathan
- Amir K Ziabari
- Diana E Hun
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- Vincent Paquit
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- Nedim Cinbiz
- Nolan Hayes
- Obaid Rahman
- Peter Wang
- Ryan Kerekes
- Sally Ghanem
- Todd Thomas
- Tony Beard
- Xiuling Nie

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

Often there are major challenges in developing diverse and complex human mobility metrics systematically and quickly.

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

The lattice collimator places a grid of shielding material in front of a radiation detector to reduce the effect of background from surrounding materials and to enhance the RPM sensitivity to point sources rather than distributed sources that are commonly associated with Natur

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

ORNL will develop an advanced high-performing RTG using a novel radioisotope heat source.

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).

Technologies for optimizing prefab retrofit panel installation using a real-time evaluator is described.