At the final (and all-day) meeting of #NYCastroML we discussed time-series analysis, including spectral analysis, filtering, and Bayesian inference. This was followed by a hack session during which I met with Schiminovich and his group to discuss GALEX photons and Rutger van Haasteren (Caltech) and Michele Vallisneri (Caltech) to discuss application of our HODLR linear algebra tools to gravitational wave detection.
The day ended with Lia Corrales (Columbia) giving a short seminar on x-ray studies of dust, where forward scattering permits (in principle) inference of the distribution of dust in space and also grain size. The talk made me think that if you could have many x-ray point sources measured (and good knowledge of the point-spread function), you could in principle fully map the dust in three-space, and also figure out the three-dimensional positions of all the point sources. Probably not feasible, but interesting to think about.