Santiago E. Cortés-Gómez

Mathematician/ Machine learning engineer.

scortesg@andrew.cmu.edu

Pittsburgh, Pennsylvania

I am a Machine Learning PhD student in the School of Computer Science at Carnegie Mellon University advised by professor Bryan Wilder. My main interest is in quantifying uncertainty in models, data and the optimization process surrounding machine learning pipelines involved in data-driven decision making. My ultimate goal is to apply my research to real world problems that affect the less fortunate, my true passion is to maximize the positive outcome of my work to society. My previous gig was as machine learning engineer at Factored.ai, a company part of Andrew Ng’s AI Fund ecosystem. During my time in the industry, I have developed deep learning applications, specially in computer vision, that overcome common problems (such as data quality and lack of computational power) faced outside the big techs companies. The techniques and specifics of each one of the aforementioned projects can be found in my CV. I hold a B.Sc. and a M.Sc., both in Mathematics from Universidad de Los Andes (2017, 2018).

News

Apr 24, 2021 Acepted paper to Bulletin of Mathematical Biology
Oct 24, 2020 Acepted paper to ML4D workshop (Neurips 2020), selected for contributed talk.
Aug 21, 2019 Andrew Ng’s AI Fund officially launchs a Medellin office!:rocket: :smile:

Selected publications

  1. Neurips
    Unsupervised learning for economic risk evaluation in the context of Covid-19 pandemic (Selected for contributed talk)
    Cortes, Santiago, and Quintero, Yullys M
    Neurips ML4D workshop 2020
    HTML PDF
  2. Bull. Math. Biol
    Alternative Strategies for the Estimation of a Disease’s Basic Reproduction Number: A Model-Agnostic Study
    Páez, Gustavo Nicolás, Cerón, Juan Felipe, Cortés, Santiago, Quiroz, Adolfo J, Zea, José Fernando, Franco, Camila, Cruz, Érica, Vargas, Gina, and Castañeda, Carlos
    Bulletin of Mathematical Biology 2021
    PDF