Columbia engineers have developed a machine-learning algorithm that will aid in understanding and mitigating the impact of extreme weather events, which are becoming more frequent in our warming climate.

As director of the Learning the Earth with Artificial Intelligence and Physics (LEAP) Center, Pierre Gentine is aiming to bring greater precision to climate modeling and innovative solutions to the climate crisis.

Kara Lamb discusses her research using machine learning to study cirrus clouds and how it can increase the accuracy of climate models.

Glacier modeling techniques that involve artificial intelligence can produce high fidelity results to a large number of questions much more quickly than traditional approaches.

A new artificial neural network named CALFIN catalogues the rates at which glaciers are melting, demonstrating what the future of glaciology could look like.

A Columbia team is pioneering a machine learning-based imaging and sorting solution that would help to drastically reduce Africa’s tsetse population.

A new study uses machine learning to better represent clouds in climate models, which helps to predict the climate’s response to rising levels of greenhouse gases.

Artificial intelligence is helping us manage the impacts of climate change and protect the environment in many ways.