Do you know Google Summer of Code? It’s a time of year when students can contribute to open-source software by developing and adding much needed functionalities to the open-source package of their choice. And Demetri Pananos did just that.
He did it in 2019 with PyMC3, for which he developed the API for ordinary differential equations. In this episode, he’ll tell us why and how he did that, what he learned from the experience, and what the strengths and weaknesses of the API are in his opinion.
Demetri is a Ph.D candidate in Biostatistics at Western University, in Ontario, Canada. His research interests surround machine learning and Bayesian statistics for personalized medicine. He earned his Master’s in Applied Mathematics from The University of Waterloo and is a firm believer in open science, interdisciplinary collaboration, and reproducible research. 
Other than that, he loves plotting data and drinking IPA beer – well, who doesn’t?”
Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ (https://bababrinkman.com/) !
Links from the show:
Demetri on Twitter: https://twitter.com/PhDemetri (https://twitter.com/PhDemetri)
Demetri on GitHub: https://github.com/Dpananos (https://github.com/Dpananos)
Demetri's website: https://dpananos.github.io/ (https://dpananos.github.io/)
PyMC3, Probabilistic Programming in Python: https://docs.pymc.io/ (https://docs.pymc.io/)
Chris Bishop, Pattern Recognition and Machine Learning: https://www.amazon.fr/Pattern-Recognition-Machine-Learning-Christopher/dp/0387310738 (https://www.amazon.fr/Pattern-Recognition-Machine-Learning-Christopher/dp/0387310738)
Bayesian Data Analysis (Gelman, Carlin, Stern, Dunson, Vehtari, Rubin): http://www.stat.columbia.edu/~gelman/book/ (http://www.stat.columbia.edu/~gelman/book/)
Parallel Plots: https://arviz-devs.github.io/arviz/generated/arviz.plot_parallel.html (https://arviz-devs.github.io/arviz/generated/arviz.plot_parallel.html)



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