Skip to main content

Machine Learning

We use machine learning algorithms to parameterize models to make useful predictions from theoretical and experimental data.  Examples include predicting new experimental conditions for high-yield catalysis and developing parameterized approximations for electronic structure methods.  Chemistry has a long and rich history of using parameterization from data to understand the world around us and machine learning is the modern continuation of this tradition.