Leonid Vaserstein, emeritus professor of mathematics, created the Wasserstein metric—a distance measurement for comparing groups of data or probabilities that is used in data science, machine learning, and AI. Rather than condensing data into a single metric like an average, the metric allows for the comparison of distributions of data. Foundational to today’s AI models, the metric is widely used in statistics and mathematics and has become increasingly popular as its intensive calculation has been streamlined by modern computational technology.