Michael Wawrzoniak will present his preFPO on Wednesday October 24 at 10AM in Room 402. The members of his committee are: Larry Peterson, advisor; David Blei, Andrea LaPaugh, Vivek Pai, and Rob Schapire. Everyone is invited to attend his talk. His abstract follows below. ---- The role played by data analysis and machine learning continues to gain significance in many fields, and society as a whole. In particular, statistical learning in the framework of graphical models has become a very successful and popular machine learning method used in many fields. However developing these models requires substantial expertise and applying them to very large distributed and streaming data sets can still be a very challenging problem. In this talk I will propose an architecture which will make a substantial subset of these techniques accessible to users with less expert machine learning knowledge. A framework for high-level description of models in conjugate-exponential family, automatically transforming them to distributed streaming stochastic variational inference procedure, and an evaluation platform will be outlined. The vision of this software stack is to show a possible future path for a shift from data analysis being in the hands the expert elites towards empowering the wider public. ----