Introducing our new Astronomy Curriculum Developer

Dr. Allen Downey joins The Carpentries as Astronomy Curriculum Developer. Welcome!

We are ecstatic to welcome Dr. Allen Downey as our new Astronomy Curriculum Developer! Allen’s role is supported by a grant from the American Institute of Physics. His work will focus on developing a set of 3-4 Carpentries-style lessons on data organisation, data management, interactive data visualisation, and publishing data for longevity and interactivity - targeted towards astronomers. Allen will join the team part-time over the next six months to develop and pilot test these lessons. Welcome to the team Allen!

Message from Dr. Allen Downey

I am looking forward to working with The Carpentries to develop a new curriculum in Astronomy. I have been a fan of The Carpentries for a long time, even more so since I completed instructor training last summer.

I have been teaching at the college level since 1990, as a graduate student at Massachusetts Institute of Technology and University of California, Berkeley, then as a professor at Colby College, Wellesley College, Olin College, and Harvard University, all in the eastern United States. I teach classes related to computer science, data science, physical modeling, digital signal processing, and engineering design.

I write books on software and data science including Think Python, Think Stats, Think Bayes and Modeling and Simulation in Python. All of these books are available under free licenses from Green Tea Press. Most recently, I developed a introductory Data Science curriculum and I am working on a gentle introduction to Bayesian Statistics, both using Python and Jupyter.

Since 2009, I have led workshops at conferences like PyCon and SciPy, using many of the same methods as Carpentries workshops and a similar philosophy. I have also developed online classes for Flatiron School and DataCamp.

I am not an astronomy expert, but I am looking forward to learning more by working on this project. I followed with interest the detection of gravitational waves with LIGO (especially because they used Python and Jupyter) and the imaging of a black hole (especially because they used Bayesian inference). We are still in the early stages of planning the new astronomy curriculum, but I hope we will be able to include some examples like this.

Dialogue & Discussion