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Annalisa Bracco, Taka Ito, and Chris Reinhard from the School of Earth and Atmospheric Sciences will create computer models to measure how well CO2 removal techniques work on land, rivers, and oceans, as part of $264 million in grants.
In a landmark study led by Georgia Tech, researchers demonstrate a first-of-its kind way to synthesize amino acids that uses more carbon than it emits.
Georgia Tech researchers introduced a groundbreaking machine learning technique to improve the assessment and analysis of declining oxygen levels in the ocean.
Led by School of Earth and Atmospheric Sciences Professor Greg Huey, the NSF RAPID grant is for analyzing air chemistry data collected during a three-week span when a chemical plume impacted the Atlanta area.
The Georgia Tech-led study captures two lizard species adapting in response to competition. The study provides some of the clearest evidence to date of evolution in action.
A Georgia Tech-led review paper recently published in Nature Reviews Physics is exploring the ways machine learning is revolutionizing the field of climate physics — and the role human scientists might play.