The day started with a discussion with So Hattori about finding single transits in the Kepler data. We did some research and it seems like there may be no clear sample in the published literature, let alone any planet inference based on them. So we are headed in that direction. In group meeting, Foreman-Mackey told us about his approach to exoplanet search, Goodman told us about his approach to sampling that uses (rather than discards) the rejected likelihood calls (in the limit that they are expensive), and Vakili told us about probabilistic PSF modeling. On the latter, we had requests that he do something more like train and test.
A fraction of the group had lunch with Brian McFee (NYU), the new Data Science Fellow. McFee works on music, from a data analysis perspective. His past research was on song selection and augmenting or replacing collaborative filtering. His present research is on beat matching. So with the two put together he might have a full robot DJ. I have work for that robot!