Penn State's Center for Astrostatistics is continuing its annual Summer Schools in Statistics for astronomers
designed for graduate students and researchers in astronomy.
This is being supplemented with a new additional week-long Summer School in Astroinformatics.
Lectures and tutorials are presented by a team of experienced professors in statistics, astronomy, computer science, and informatics.
Classroom instruction is interspersed with hands-on analysis of astronomical data with opportunity for discussion of methodological issues.
|Summer School in Statistics for astronomers
||Summer School in Astroinformatics |
Principles of probability and inference
Model selection & validation
Maximum likelihood methods
Clustering and classification
Fundamentals of scientific computing
Machine Learning algorithms
Clustering & classification
Gaussian Process regression
Neural Networks & Deep Learning
The 2018 summer school in statistics for astronomers will be modeled on 2017 & earlier Penn State summer
schools since 2005, and the three Indian Institute of
Astrophysics-Penn State summer schools.
The 2017 summer school will be held on the
Pennsylvania State University's
University Park Campus located in State
College, Pennsylvania, USA. The town
College and the university campus
combine to offer a relaxed, college town atmosphere with many shops,
restaurants and points
of interest. Recreational opportunities abound including fine golf
courses, tennis courts, gymnasiums and swimming
facilities. For local information
visit the Central
Visitors Bureau online.
Software & Computer Account Setup:
Participants in the first week (Astrostatistics): The tutorials will depend on students using “R” on their own laptops. Please download and install R from http://www.r-project.org.
Participants in the second week (Astroinformatics): Exercises will use a variety of languages (R, Python, Julia, C/C++), language extensions (e.g., OpenMP, OpenACC), and packages (e.g., scikit-learn, STAN). In order to ensure all participants have access to a common software stack and datasets, the tutorials will depend on students using their own laptops to access supercomputing resources via XSEDE and working in Jupyter notebooks with our custom software stack via SciServer.org. Please create accounts on the XSEDE and SciServer.org systems.
When testing your terminal emulator, run the command "ssh" to insure it has been installed. Further instructions will be provided after all participants accounts have been activated on XSEDE.
- To create an XSEDE account, go to https://portal.xsede.org/#/guest, click the "Create Account" button on the left, and follow the instructions.
To create an account on SciServer.org, go to https://alpha02.sciserver.org.
Once you have created both accounts, submit your usernames on each of those systems via the form at https://goo.gl/forms/ILpThKmCbt70lZku1. Please submit your usernames by May 21 to ensure that you will have access to all the course materials needed.
Ensure that your laptop has access to a terminal emulator and ssh.
- Microsoft Windows: Get PuTTY from https://www.putty.org
Mac OSX: Terminal program and ssh should be built in. ( Applications -> Utilities -> Terminal)
Linux: Terminal program should be built in, usually under System Tools.