[JSoC 2021] Student Introduction. Improve different aspects of MCMCChains.jl

I’m Paulina Martin and this summer I’ll be working as a GSoC student on the MCMCChains improvements project for the Turing ecosystem. I’m a Biology student from Mexico that got interested in Physics, Programming and Mathematics. Currently, I’m taking the last steps to finish my undergraduate degree in Biology, while simultaneously studying Physics as a second undergraduate degree. As a future goal, I want to be a researcher in Biophysics, so I can study the physics behind biological phenomena, especially those in Ecology, Evolution and Quantum Biology.

With Cameron Pfiffer and Hong Ge as mentors, this summer I’ll carry out various tasks to improve different aspects of MCMCChains.jl. Inside the Turing ecosystem, MCMCChains.jl represents an implementation of Julia types for analyzing, storing and summarizing MCMC simulations and uses utility functions for diagnostics and results visualization. In particular, my project aims to make visual improvements to plotting, add convenient plot defaults especially when plotting numerous parameters, integrate new plot types into MCMCChains environment, implement a non-serialized based method to save MCMC chains sampling, and improve the available documentation of MCMCChains.

I’m really excited to be part of the JSoC this summer and to join the Julia Lang community!
Cheers and have a great day.


Fantastic! I’ve been using Stan with rstan for a bayesian data analysis course (Julia was not an option). And great as it is, I really realised how spoilt I am with Julia based PPLs. However, using Bayesplot did get me thinking that we need better plotting options for Turing. I was literally thinking about that this morning. Really happy to hear that someone is working on this. It’s much appreciated.


Welcome! We are super glad to have you.

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