What is computational data analysis? Any analysis done via computer. If that seems absurdly broad, that’s because it is. Data is itself a broad catch all for any collection of stuff-written, audio, visual, kinetic, etc.-that someone wants to analyze. Sometimes the data is such that it can directly be mapped into some visual representation, but often it also has stories that can be uncovered via mathematical/statistical/network (graph theoretic)/etc. analysis. The analysis does not really care what discipline the data is form so long as it can be manipulated into a form that can be run through the algorithm. The algorithm yields numbers or graph nodes or the like, and then it’s often the job of visualization to map those results back into something contextualized by the domain. On Wednesday Nov 15th, Michael Waskom-creator of the Seaborn statistical visualization package-will give a talk on the role of visualization in computational data analysis. It is open to the public and we hope you come: The Role of Visualization in Computational Data Analysis