Researchers have developed a methodology to determine why coastal glaciers are retreating, and in turn, how much can be attributed to human-caused climate change.
Ph.D. student Phillip Si and Assistant Professor Peng Chen developed Latent-EnSF, a technique that improves how ML models assimilate data to make predictions.
Through a new review paper published in Nature, Georgia Tech scientists are revealing how decades-long research programs have transformed our understanding of evolution, uncovering secrets that would remain hidden in shorter studies.
A new study explores how complex chemical mixtures change under shifting environmental conditions, shedding light on the prebiotic processes that may have led to life on Earth.
Whether trying to design secure sensor networks, mine data or use origami to deploy satellites, the underlying language and ideas are likely to be that of topology.
CEE researchers’ analysis outlines path to a U.S. construction market for hemp-based fibers, which are already used for clothing and biodegradable plastics.
The fires enabled the first real-time data on airborne lead, thanks to a pioneering air quality measurement network.
Professor Yongsheng Chen leads a multi-university team using machine learning to discover PFAS-removing membranes.
Georgia Tech recently achieved a STARS silver rating by the Association for the Advancement of Sustainability in Higher Education (AASHE).
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.