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Researcher
- Ryan Dehoff
- Singanallur Venkatakrishnan
- Vincent Paquit
- Amir K Ziabari
- Diana E Hun
- Michael Kirka
- Philip Bingham
- Philip Boudreaux
- Stephen M Killough
- Aaron Werth
- Adam Stevens
- Ahmed Hassen
- Alex Plotkowski
- Alice Perrin
- Ali Passian
- Amit Shyam
- Andres Marquez Rossy
- Blane Fillingim
- Brian Post
- Bryan Maldonado Puente
- Christopher Ledford
- Clay Leach
- Corey Cooke
- David Nuttall
- Emilio Piesciorovsky
- Gary Hahn
- Gina Accawi
- Gurneesh Jatana
- Harper Jordan
- James Haley
- Jason Jarnagin
- Joel Asiamah
- Joel Dawson
- Mark M Root
- Mark Provo II
- Nance Ericson
- Nolan Hayes
- Obaid Rahman
- Patxi Fernandez-Zelaia
- Peeyush Nandwana
- Peter Wang
- Rangasayee Kannan
- Raymond Borges Hink
- Rob Root
- Roger G Miller
- Ryan Kerekes
- Sally Ghanem
- Sarah Graham
- Srikanth Yoginath
- Sudarsanam Babu
- Varisara Tansakul
- Vipin Kumar
- Vlastimil Kunc
- William Peter
- Yan-Ru Lin
- Yarom Polsky
- 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.

The ever-changing cellular communication landscape makes it difficult to identify, map, and localize commercial and private cellular base stations (PCBS).

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.

Electrical utility substations are wired with intelligent electronic devices (IEDs), such as protective relays, power meters, and communication switches.

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).