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.



Subpages (2): Causal Inference Teaching
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Valeria Espinosa,
Nov 13, 2013, 7:15 AM
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Valeria Espinosa,
Nov 5, 2013, 7:28 AM