Discussed MCMC convergence with Jeffrey Gertler (NYU), Bayesian evidence (fully marginalized likelihood) with Hou and Goodman, and data-science projects with Mike O'Neil (NYU). O'Neil is co-teaching a course at NYU for the new Data Science program, where the idea is that Masters students will do research projects on real research topics. Foreman-Mackey and I are happy to provide; we discussed several ideas, most of which involve the Kepler data, which we have on the brain right now. One idea is to find all the single transits and see if you can use them to place limits on (or measure!) the frequency (suitably defined) of Jupiter analogs (suitably defined). That's a great problem to post on my Ideas Blog. Hou is computing the marginalized likelihoods of various qualitatively different explanations of radial velocity data, including stellar oscillation models and multi-planet scenarios. Gertler is preparing to find exoplanets in the Galex photon (time-resolved) data.