Robust optimization (RO) is a useful methodology for formulating optimization problems in which some parameters are uncertain, but belong to a given uncertainty set. Two-stage RO models have received substantial attention in various application domains because of their ability to provide robust, reliable, and adaptable solutions. However, they are often challenging to solve. In this talk, I will introduce innovative and computationally efficient column-and-constraint generation (C&CG) algorithms for solving two-stage RO problems. C&CG algorithms operate within a master-subproblem framework. .