Why Your Field Needs a Hack Week: Bringing Data Science Into Astronomy



Daniela Huppenkothen

Moore-Sloan Postdoctoral Fellow, Center for Data Science, New York University

Daniela Huppenkothen is a Moore-Sloan postdoctoral fellow at the NYU Center for Data Science. She is primarily interested in time series methods for astronomy. So far, her work has focused on developing methods for characterizing variability in fast transient events (in particular magnetar bursts) in data from X-ray space telescopes and on using Bayesian statistics to make inferences about the underlying physics of the system. She is also interested in machine learning and astrostatistics.