Computational statistics, or statistical computing, is the interface between statistics and computer science. It is the area of computational science (or scientific computing) specific to the mathematical science of statistics. The availability of personal computer, computational software, and visual representations of data enables the managers to concentrate on the revealing useful facts from figures. Since the burden of computation has been eliminated, the managers are now able to focus on probing issues and search for creative decision-making under uncertainty. The last twenty years has witnessed nothing short of a digital data deluge. Modern data have become both voluminous as well as high dimensional creating an urgent need to revise classical inferential techniques. In addition to the need for new theory, computationally efficient and scalable algorithm development has become an exciting new frontier for innovating statistical methodology. Faculty in the computational statistics group are developing numerically sound optimization and sampling algorithms to fit models that exploit inherently low-dimensional structure in high-dimensional big data.