About Me

I’m a rebel physicist/engineer who loves statistical data analysis. By day, I am currently a Research Assistant on Bayesian Model Selection with David Rossell at UPF, Barcelona. By night I am a core developer of ArviZ a Python package for exploratory analysis of Bayesian models. In addition to data analysis probabilistic modeling, I also love programming and teaching.

I think that the culture in scientific research needs deep changes towards a more collaborative, open and diverse model. I am interested in open science, reproducible research and science communication. I want to pursue a career in probabilistic modeling and statistical research with special emphasis on openness and reproducibility.

In my spare time, I like playing board games and going to the beach to do water activities. I have been sailing and snorkeling regularly since I was little and more recently I added kayaking to the mix too! I generally spend the summer at the Costa Brava. Here I leave you a sneak peak of the views when nobody is around



  • PyMCon 2020: PyMCon 2020 is an asynchronous-first virtual conference for the Bayesian community

Open source work

Here are highlighted some open source projects I contribute to, check out my GitHub profile for a complete list of the projects I contribute to.

  • ArviZ: Exploratory analysis of Bayesian models in Python or Julia
  • mombf: Bayesian model selection and averaging for regression and mixtures for non-local and local priors.
  • exosherlock: Smooth your interactions with the NASA Exoplanet Archive using Python and pandas.
  • PyMC3/4: Friendly probabilistic programming in Python.

Talks and conferences

  • PROBPROG 2020: Coming on autumn 2020
  • StanCon 2020: ArviZ, InferenceData, and NetCDF: A unified file format for Bayesians. Slides and video presentation are available at GitHub, the slides are executable thanks to Binder!


  • M. Badenas-Agusti, M. N. Günther, T. Daylan, et al., 2020, HD 191939: Three Sub-Neptunes Transiting a Sun-like Star Only 54 pc Away
  • D. Foreman-Mackey, W. Farr, M. Sinha, A. Archibald, et al., 2019, emcee v3: A Python ensemble sampling toolkit for affine-invariant MCMC.