Ethan Ancell set out on an ambitious journey to rewrite the code for a previously existing machine-learning method to develop a better model to measure soil moisture across Utah.

“Many ecological and spatial processes, like the amount of soil moisture, are complex in nature and are not accurately modeled by linear models,” says Ancell, a dual statistics and computational mathematics major. “Regression trees, which are predictive modeling approaches, promise to handle the high-order interactions present in ecological and spatial datasets, but fail to produce physically realistic characterizations of the underlying landscape.”

Read about Ethan's Research