Alfredo Garbuno Iñigo

Advanced Analytics.


ITAM, Mexico City.

I was the academic director of the Msc in Data Science and an assistant professor at Instituto Tecnológico Autónomo de México (ITAM). I taught courses for the Department of Statistics and the masters program in Data Science at ITAM. I currently hold an appointment at level 1 by the National System of Research (SNI) from Mexico's National Council of Science and Technology (CONACyT). I have also been elected as member of the Board of Directors for the Latin American Regional Section (LARS) of the International Association for Statistical Computing (IASC).
My main line of research is on Uncertainty Quantification (UQ) which typically involves computationally expensive computer codes that are run on high performance computing environments. My research also deals with algorithmic approximations and their theoretical analysis in order to properly quantify related uncertainties. Overall my areas of expertise are Bayesian inference, Bayesian Inverse problems, Data Assimilation, Predictive Modeling, Resampling methods, and, lately, Conformal predictions. Part of my research has been developed and incorporated on the project of the Climate Modeling Alliance (CliMA).
I am an advocate of modern computing technologies. I am particularly proud of incorporating remote computing environments for my students at both undergraduate and graduate leves. These computing environments are set in such a way that mimics the typical infrastructure available for Big Data applications. My opinion is that these skills are a necessity for the new generation of statistics--oriented and --assisted research. I believe these particularities are shaping the future of Statistics as a modern discipline.

Academic Background

I was a postdoctoral scholar at the California Institute of Technology (Caltech) during 2018-2020. It was a dual position in the Computing and Mathematical Siences (CMS) and the Environmental Science and Engineering (ESE) departments. I received my PhD from the University of Liverpool while doing research at the Institute for Risk and Uncertainty + School of Engineering. My dissertation focused on non-parametric Bayesian Statistics in computer code analysis driven by Gaussian processes, Bayesian inference and automatic calibration. I obtained my Masters in Data Science at ITAM (Instituto Tecnológico Autónomo de México). I have a Bachelor degree in both Applied Mathematics and Actuarial Sciences. To learn about my teaching experience please visit here.


Oct 3, 2023 I have decided to move onto a new job opportunity at BBVA Mexico. I will be leading the Advanced Analytics discipline in light of a massive migration to cloud services and ever growing team of Data Scientists.
Mar 14, 2023 I have been elected as a member of board of directors (BoD) of the latin american regional section (LARS) of the International Association for Statistical Computing (IASC).
Feb 28, 2023 I am part of the local organizing committee of the annual meeting of SIAM Mexican Chapter taking place at ITAM (more info here).
Dec 14, 2022 Two of my advisees in the Msc got graduated. See a brief description of their work on inflation forecasts and vaccine effects.
May 26, 2022 The first undergrad I mentored defended her dissertation. More details here.

selected publications

  1. CES
    Calibrate, Emulate, Sample
    Cleary, Emmet, Garbuno-Inigo, Alfredo, Lan, Shiwei, Schneider, Tapio, and Stuart, Andrew M
    Journal of Computational Physics 2021
  2. EKS
    Interacting Langevin Diffusions: Gradient Structure and Ensemble Kalman Sampler
    Garbuno-Inigo, Alfredo, Hoffmann, Franca, Li, Wuchen, and Stuart, Andrew M
    SIAM Journal on Applied Dynamical Systems 2020