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Researcher
- Ryan Dehoff
- Singanallur Venkatakrishnan
- Vincent Paquit
- Amir K Ziabari
- Diana E Hun
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- Andres Marquez Rossy
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- Sarah Graham
- Sudarsanam Babu
- Vipin Kumar
- Vlastimil Kunc
- William Peter
- Yan-Ru Lin
- Ying Yang
- Yukinori Yamamoto

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

Mechanism-Based Biological Inference via Multiplex Networks, AI Agents and Cross-Species Translation
This invention provides a platform that uses AI agents and biological networks to uncover and interpret disease-relevant biological mechanisms.

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

High strength, oxidation resistant refractory alloys are difficult to fabricate for commercial use in extreme environments.

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

In manufacturing parts for industry using traditional molds and dies, about 70 percent to 80 percent of the time it takes to create a part is a result of a relatively slow cooling process.

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).

This technology combines 3D printing and compression molding to produce high-strength, low-porosity composite articles.