Modern Statistical and Computational Methods for Analysis of Kepler Data

Greetings from Research Triangle Park, North Carolina.  For the next two weeks, I’ll be hanging out at the Statistical and Applied Mathematical Sciences Institute (SAMSI) for the Modern Statistical and Computational Methods for Analysis of Kepler Data mini-research program.

SAMSI’s goal is “to forge a synthesis of the statistical sciences and the applied mathematical sciences with disciplinary science to confront the very hardest and most important data- and model-driven scientific challenges.”  This particular 3 week program (I’m staying two weeks since I have to be in Hawaii for my observing run on June 28th), is to bring together astronomers, statisticians, and computer scientists to come up with new and interesting ways to tackle the questions and current challenges in the field of extrasolar planets with Kepler data.

I’m giving one of the invited talks today  presenting on applying a citizen science approach to the Kepler data set  highlighting Planet Hunters science. After the two days of talks from invited speakers, on Wednesday we’ll break into mini-research groups. I’ve come with a subset of the Planet Hunters classification database (No usernames or emails are listed. The only identifying information for a volunteer is an identification number to link classifications) to hopefully learn and develop some new methods and algorithms  to combine your classifications and better search for planet transits.

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Yesterday I gave a talk at the 223rd American Astronomical Society meeting titled ‘Planet Hunters: Kepler by Eye’  at the National Harbor outside of Washington, DC. The talk gives a brief overview of