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Researcher
- Singanallur Venkatakrishnan
- Vincent Paquit
- Amir K Ziabari
- Andrzej Nycz
- Diana E Hun
- Kuntal De
- Philip Bingham
- Philip Boudreaux
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- Xiaohan Yang
- Alex Walters
- Biruk A Feyissa
- Bryan Maldonado Puente
- Chris Masuo
- Clay Leach
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- Debjani Pal
- Gerald Tuskan
- Gina Accawi
- Gurneesh Jatana
- Ilenne Del Valle Kessra
- Mark M Root
- Michael Kirka
- Nolan Hayes
- Obaid Rahman
- Paul Abraham
- Peter Wang
- Ryan Kerekes
- Sally Ghanem
- Vilmos Kertesz
- Yang Liu

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.

We present the design, assembly and demonstration of functionality for a new custom integrated robotics-based automated soil sampling technology as part of a larger vision for future edge computing- and AI- enabled bioenergy field monitoring and management technologies called

Detection of gene expression in plants is critical for understanding the molecular basis of plant physiology and plant responses to drought, stress, climate change, microbes, insects and other factors.

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

Due to a genes unique nucleotide sequences acquired through horizontal gene transfer, the gene has a transcriptional repressor activity and innate enzymatic role.

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.

The invention provides on-line analysis of droplets for mass spectrometry.