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Summer School in Statistics for Astronomers XIV

Penn State's Center for Astrostatistics is supplementing its long-standing week-long Summer School in statistical methodology with a new Summer School in Astroinformatics. Registration is now open; participants can attend one or both of the programs. Lectures and tutorials are presented by professors in statistics, computer science, astrostatistics and astroinformatics. Tutorials exercise methods with realistic contemporary astronomical dataset. Open-source software and lecture notes are provided. Participants should bring a laptop computer.
Quando 29/05/2018 a 00h00 11/06/2018 a 00h00 a
Onde Penn State University
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Summer School in Statistics for Astronomers XIV  (May 29-June 2 2018)

Summer School in Astroinformatics (June 4-8 2018)

Penn State University

School information and detailed program


Summer School in Statistics for Astronomers  This week provides an intensive program in statistical inference and methods for observational astronomy.  Topics include: principles of probability and inference; nonparametrics; regression and model selection;  bootstrap resampling; maximum likelihood; Bayesian inference; multivariate clustering and classification; spatial statistics; and time series analysis. Hands-on training uses the R statistical software environment.

Week 1 instructors

G. Jogesh Babu, Distinguished Professor, Statistics, Penn State

Eric Feigelson, Professor, Astronomy & Astrophysics and Statistics, Penn State

Murali Haran, Professor, Statistics, Penn State

David Hunter, Professor and Head, Statistics, Penn State

Bing Li, Professor, Statistics, Penn State

Thomas Loredo, Senior Research Associate, Astronomy, Cornell University

Chad Schafer, Associate Professor, Statistics, Carnegie-Mellon University

 

Summer School in Astroinformatics   This week gives a strong background in statistical and computational methodology for large astronomical datasets.  Topics include: fundamentals of scientific computing and high-performance computing; Bayesian computation; machine learning algorithms; multivariate dimension reduction; clustering and classification; optimization; Gaussian Processes regression; neural networks and Deep Learning.  

Week 2 instructors

Senior staff, Institute for Cyberscience, Penn State

Le Bao, Assistant Professor, Statistics, Penn State

Tamas Budavari, Assistant Professor, Applied Mathematics and Statistics, Johns Hopkins

Jessi Cisewki-Kehe, Assistant Professor, Statistics and Data Science, Yale

Ethan Fang, Assistant Professor, Statistics, Penn State

Lee Giles, Distinguished Professor, Informations Sciences & Technology, Penn State

Vasant Hanovar, Distinguished Professor, Informations Sciences & Technology, Penn State

Murali Haran, Professor, Statistics, Penn State

Jia Li, Professor, Statistics, Penn State

Angie Wolfgang, NSF Postdoctoral Fellow, Astronomy & Astrophysics, Penn State

Lingzhou Xue, Assistant Professor, Statistics, Penn State

  

Registration and further information:   http://astrostatistics.psu.edu/su18

Registration deadline:  May 4 2018 or when the classes are full

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