Data science for astronomy

In the last few years, there has been an increased interest towards computer applications for astronomical research. This interest is mainly triggered by the ongoing and future observational projects expected to deliver huge amounts of high-quality data, which needs to be promptly analyzed. Some illustrative examples are: the upcoming Large Synoptic Survey Telescope (LSST), the ongoing Vista Variables in the Via Láctea (VVV) ESO Public Survey, and the Atacama Large Millimeter/submillimeter Array (ALMA), among others. Besides the upcoming telescopes, today we have hundreds of astronomical catalogs of tens of millions of objects, available online. All this information makes the Astronomical analysis of stellar objects impossible without the help of computer systems. Last advances in data science, Machine Learning, and Statistics offer us very powerful solutions to explore Astronomical data, nevertheless, there are many challenges that we still need to overcome. In this talk I will present a summary of our main work in time series automatic classification, light-curve representation, automatic detection of specific types of stars, discovery of unknown classes of stellar objects and meta models for efficient and automatic integration of trained experts.