Robust decision making under uncertainty is of fundamental importance to numerous disciplines and application areas. For many practical issues, decision making often involves multiple, often conflicting, goals and poses challenging optimization problems. Recent innovations underlying multiple objective optimizations, in the characterization, quantification, and subsequently reduction of uncertainties, and in the ability to develop and apply these methods outside the traditional application domains greatly enhances their utility and promise. The main focus is to develop systematic methods, algorithms, and approaches for rapid, reliable, and robust multiple objective optimal decisions making under uncertainty and to successfully apply these methods to diverse application areas. We harness multidisciplinary expertise in the areas of modeling & simulation, visualization, optimization, uncertainty analysis, manufacturing, process design and control, environmental and ecosystem management, security systems analysis, and operation research. Our discipline independent nature allows us to collaboratively address research challenges in various fields.