Jasper Lee joined UW-Madison as a postdoc in August 2021, mentored by Ilias Diakonikolas in the Department of Computer Sciences and partly supported by IFDS. He completed his PhD at Brown University, working with Paul Valiant. His thesis work revisited and settled a basic problem in statistics: given samples from an unknown 1-dimensional probability distribution, what is the best way to estimate the mean of the distribution, with optimal finite-sample and high probability guarantees? Perhaps surprisingly, the conventional method of taking the average of samples is sub-optimal, and Jasper’s thesis work provided the first provably optimal “sub-Gaussian” 1-dimensional mean estimator under minimal assumptions. Jasper’s current research focuses on revisiting other foundational statistical problems and solving them also to optimality. He is additionally pursuing directions in the adjacent area of algorithmic robust statistics.