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Predicting how the environment is going to change is vital for making decisions about how to best manage our natural resources. Advances in data and computer science give us an opportunity to make greater and better-informed forecasts, as well as gain a greater understanding of ecosystems. The Eco-KGML group (Ecology Knowledge-Guided Machine Learning) is dedicated to researching novel modeling and forecasting techniques that leverage the advantages of scientific knowledge, process-based models, and machine learning. For more information about our projects and our team, use the links above!
This project is supported in part by grants from the US National Science Foundation (#2213549, #2213550)
