Computational Astronautical Sciences and Technologies

The CAST's Fabric 
The Computational Astronautical Sciences and Technologies (CAST) group pursues research that few other research groups are positioned to address related to wicked problems of space safety, security, and sustainability, as well as generalized astronautics. In essence, the group explores problems by embracing the full physical and societal complexities via large scale computing. Instead of focusing on optimization and simplification, the focus is on completeness and rigor where the community can benefit by using the work as a datum for validating optimization and simplifications.
The CAST has the following focus areas: (a) uncertainty quantification, (b) space object motion and characterization,(c) data-driven decision intelligence (to include data engineering, science, and analytics).
The group believes: 1) Measurements yield data 2) Data follow distributions (aleatory) or have structure (epistemic) 3) Distributions or structure provide inferred models (hypotheses) 4) Models permit prediction (hypothesis testing and falsifiability principle) 5) Prediction reflects understanding (hypothesis refinement)

Data Renaisscientists 
CAST are knowledge sculptors where the block of enslaving marble is ignorance, the tools to chip away at the ignorance are data. In order to sculpt these knowledge statues, the group makes use of abductive reasoning. Much like a refrigerator indirectly cools by incrementally removing heat over time, CAST seeks to learn by incrementally removing ignorance over data. In this process Karl Popper's Falsifiability Principle is applied in that only hypotheses shown by the evidence to be false are removed. What remains is not guaranteed to be true but does explain the evidence in hand, and thus by measures possible.