There were far too many interesting projects to list here, but the following is a small sample: In her talk, titled “Why Your Field Needs a Hack Week: Bringing Data Science Into Astronomy,” Daniela discussed the ideas behind Astro Hack Week and how similar concepts might be applied to other fields.įinally, on Friday afternoon, we wrapped up the week by presenting the results of everyone’s projects during the week. On Friday, one of the week’s organizers, Daniela Huppenkothen, gave the BIDS Data Science Lecture. This year, we had breakouts on Gaussian Processes, databases, automatic differentiation, packaging and documentation in Python, Git and GitHub, and hierarchical Bayesian inference. Scattered throughout the afternoons were breakout sessions: optional ad hoc lectures on popular topics selected by popular vote by participants during the week. While these mornings were typical of a summer school, the rest of the week (afternoons, evenings, and all day Friday) were broadly unstructured: the approximately 50 participants formed small groups and worked together on collaborative research projects, applying concepts covered during the morning sessions to real astronomy research problems. Astro Hack Week is a summer school and collaborative workshop, the goal of which is to apply modern techniques in statistics, machine learning, and computing to problems in astronomy.Īstro Hack Week has a distinctive format: Monday through Thursday mornings consisted of in-depth lectures on topics in statistics and machine learning. BIDS hosted the third annual Astro Hack Week during the week of August 29–September 2.