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Leonard E Parker

Center for Gravitation, Cosmology & Astrophysics

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Leonard E Parker Center for Gravitation, Cosmology and Astrophysics

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The Leonard E Parker Center for Gravitation, Cosmology and Astrophysics is supported by NASA, the National Science Foundation, UW-Milwaukee College of Letters and Science, and UW-Milwaukee Graduate School. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of these organizations.

Summer Studies in the CGCA

Posted by Daniel Mashburn on August 22, 2014


This year there have been a lot of advances by corporations such as Google and IBM in teaching machines to think like people. A self-organized set of students collaborated over the past few months to learn techniques in astronomical statistics, data mining and machine learning. The idea was generated by group of Madison students and propelled forward by individuals here eager to learn from one another.

Each weekly meeting covered roughly a single chapter from Statistics, Data Mining, and Machine Learning in Astronomy by Ivezic, Connolly, VanderPlas & Gray, all organised by Laleh Sadeghian (postdoc). Primarily graduate students and post-docs in CGCA have taught the course, but attendance has included every level of learner from undergraduate to professorial. Learning from my peers was a great opportunity, as no one is a true expert; silly questions were never ignored. When I had a turn to present, I also found the experience more rewarding. Because my audience had a similar mastery of the subject material, except of course for my particular chapte there was no need to fear that you were talking above someone’s head or beneath another’s expertise.

Many of the things I learned in class, I have put into use readily. The chapter on bootstrapping, presented by Megan DeCeaser, takes a single measurement from a few points, and performs the calculation an extra thousand times by randomly resampling your data set. Or, if you I have an over-abundance of data giving me grief, then simply reduce those discreet points to a simple hierarchal structure with an ‘extreme deconvolution,’ (see figure 1).

The advancement of computing technologies in recent decades, and its continued acceleration, ensures a need for well-trained programmers in the field of astronomy. Taking a summer course in the CGCA is a relaxed yet intensive way to learn, teach, and meet some new people who share a common goal in education and exploration. If you think hosting a summer study course is right for you, or maybe you just want to keep your research skills sharp in the long and hazy summer evenings, then get ready for next year!

Figure 1: An example of extreme deconvolution of stellar data. Image taken from http://www.astroml.org/book_figures/chapter6/index.html


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