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Researcher
- Benjamin Manard
- Alexander I Wiechert
- Costas Tsouris
- Cyril Thompson
- Stephen M Killough
- Bryan Maldonado Puente
- Charles F Weber
- Corey Cooke
- Debangshu Mukherjee
- Diana E Hun
- Gs Jung
- Gyoung Gug Jang
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- Jonathan Willocks
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- Md Inzamam Ul Haque
- Nolan Hayes
- Olga S Ovchinnikova
- Peter Wang
- Philip Boudreaux
- Radu Custelcean
- Ryan Kerekes
- Sally Ghanem
- Vandana Rallabandi

High-gradient magnetic filtration (HGMF) is a non-destructive separation technique that captures magnetic constituents from a matrix containing other non-magnetic species. One characteristic that actinide metals share across much of the group is that they are magnetic.

Among the methods for point source carbon capture, the absorption of CO2 using aqueous amines (namely MEA) from the post-combustion gas stream is currently considered the most promising.

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.

This innovative approach combines optical and spectral imaging data via machine learning to accurately predict cancer labels directly from tissue images.