Eigenvalue statistics such as the CDFs of the smallest eigenvalues of classical random matrix ensembles can be expressed with Fredholm determinants. In 2009, Bornemann introduced an efficient numerical algorithm for computing Fredholm determinants and obtained many numerical results on the eigenvalues of orthogonal polynomial ensembles. In this work, we present a numerical computation of broader statistics using conditional determinantal point processes. Our method has a number of applications such as efficient numerical computation of joint PDF of the k-largest eigenvalues, the top DR path of the Aztec diamond, and sampling of the Airy_2 process. This is a joint work with Alan Edelman (MIT).