Jake Vanderplas is an NSF post-doctoral fellow at University of Washington, working jointly between the Computer Science and Astronomy departments. His research involves applying recent advances in machine learning to large astronomical datasets, in order to learn about the Universe at the largest scales. He is co-author of "Statistics, Data Mining, and Machine Learning in Astronomy", a python-centric textbook to be published by Princeton Press in 2013, and has presented many technical talks and papers in this subject area.
In the Python world, Jake is a core maintainer of scipy, a regular contributor to scikit-learn, and the creator of astroML, a python package for machine learning in astronomy and astrophysics. He occasionally blogs on python-related topics at http://jakevdp.github.com. In what remains of his free time he enjoys hiking, cycling, triathlons, and playing bluegrass mandolin and banjo.
Thursday 9 a.m.–12:20 p.m. in Mission City M1