Row/column sampling techniques were initially introduced to compute low-rank matrix approximation faster than the computation of SVD. In this talk, I will give a quick overview of squared-length sampling, adaptive sampling, volume sampling, relevance-score sampling etc., survey their connections to other topics such as determinantal point processes, rounding Lasserre SDP solutions, graph sparsification, convex geometry, and discuss interesting open problems in these.