Speaker: Sheehan Olver Topic: Numerical Random Matrix Theory Abstract: Random matrix theory has undergone significant theoretical progress in the last two decades, including proofs on universal behaviour of eigenvalues as the matrix dimension becomes large, and a deep connection between algebraic manipulations of random matrices and free probability theory. Underlying many of the analytical advances are tools from complex analysis. By developing numerical versions of these tools, it is now possible to calculate random matrix statistics to high accuracy, leading to new conjectures on the behaviour of random matrices. We overview recent advances in this direction. Lunch: If you would like to come to lunch at the Grandstand with the speaker, please meet at 12.30 by the lifts on Level 6.