I am currently a Statistician at Google. In 2014 I finished my PhD in Statistics at Harvard University, where I was a teaching and research fellow for four years. I got my BSc in applied mathematics at ITAM in 2007, in Mexico City.
My main areas of interest are: causal inference, design and analysis of experiments, Bayesian modeling, and data visualization.
My thesis proposes a new method for analyzing experiments, which combines randomization, Bayesian and potential outcomes ideas, explores its application in different settings and has a cool applied example: directed differentiation of stems cells into beta cells (for which I also designed the experiment).
Below are the draft versions of two papers that I worked on during my PhD. The first chapter of my thesis is the paper I wrote, together with my advisors Don Rubin and Tirthankar Dasgupta, presenting this method for the unreplicated case (EDR link below). The second link is the paper Don and I wrote on the analysis of the effect of military interventions on homicide rates in the Mexican Drug War.