This special issue will focus on the intersection of Information theory with estimation and inference. Information Theory has provided powerful tools as well as deep insights into optimal procedures for statistical inference and estimation. The application of these tools include characterization of optimal error probabilities in hypothesis testing, determination of minimax rates of convergence for estimation problems, analysis of message-passing and other efficient algorithms, as well as demonstrating the equivalence of different estimation problems.