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Researcher
- Ryan Dehoff
- Venkatakrishnan Singanallur Vaidyanathan
- William Carter
- Alex Roschli
- Amir K Ziabari
- Andrzej Nycz
- Brian Post
- Chris Masuo
- Diana E Hun
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- Femi Omitaomu
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- Obaid Rahman
- Oluwafemi Oyedeji
- Rangasayee Kannan
- Roger G Miller
- Ryan Kerekes
- Sally Ghanem
- Sarah Graham
- Soydan Ozcan
- Sudarsanam Babu
- Tyler Smith
- William Peter
- Xianhui Zhao
- Yukinori Yamamoto

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 use of biomass fiber reinforcement for polymer composite applications, like those in buildings or automotive, has expanded rapidly due to the low cost, high stiffness, and inherent renewability of these materials. Biomass are commonly disposed of as waste.

We will develop an AI-powered autonomous software development pipeline to help urban scientists develop advanced research software (e.g., digital twins and cyberinfrastructure) to support smart city research and management without the need to write codes or know software engin

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