I am a first year (cotutelle) PhD student in Engineering Sciences with specialization in Math Modeling at Universidad de Chile and Computer Science at École centrale de Lille and Inria.

On my spare time I like to keep up with the state of the art on different areas so I will be writing about it in the post section and I’m also running a seminar every Sunday, where we discuss different topics with more researchers. Feel free to contact me if you want to participate.

I’m also a member of ICOVID Chile which is a group created by the universities of Chile, Católica and Concepción whose general purpose is to generate key indicators that best represent the situation of the SARS-CoV-2 pandemic.


  • Mathematical Optimization
  • Energy Systems
  • Game Theory
  • Operation Research
  • Machine Learning
  • Artificial Intelligence
  • Data Science


  • MEng with specialization in Applied Mathematics, 2019

    Universidad de Chile, Santiago.

  • Civil Engineering in Mathematics, 2019

    Universidad de Chile, Santiago.

  • BSc in Engineering with specialization in Mathematics, 2017

    Universidad de Chile, Santiago.

  • Summer courses, 2017

    Instituto de Matematica Pura e Aplicada, Rio de Janeiro.



Doctoral Researcher

Universidad de Chile, Inria Lille

Mar 2020 – Present Santiago Chile & Lille, France
Double Ph.D. program in mathematical optimization for pricing in energy markets with a massive entry of renewables energies.

Visitor Researcher

Inria Nord Europe Lille

Oct 2019 – Apr 2020 Lille, France

Research and numerical implementation of algorithms for pricing in energy markets.

  • Technologies used: Julia, Matlab

Master project

Universidad de Chile, Inria Lille

Jan 2019 – Sep 2019 Santiago Chile & Lille, France

Bi-level Nash-single stochastic follower model for modeling competition in mixed energy markets including network and capacity constraints.

  • Technologies used: Julia, Matlab


Banco Central de Chile

Dec 2017 – Feb 2018 Santiago, Chile

Working with databases. Creating and implementing a method inspired by text mining techniques and Simulated annealing in order to compute how many new job positions were created in a determined period of time.

  • Technologies used: SAS, R


Centro de Modelamiento Matemático

Jul 2017 – Dec 2017 Santiago, Chile

Reconstruction of Transcription Regulatory Networks. A method based on Steiner tree problem was developed and programmed.

  • Technologies used: Python


Centro de Investigación Avanzada en Educación CIAE

Jan 2017 – Feb 2017 Santiago, Chile
Creation and resolution of math olympiad problems for university and highschool students.


Instituto de Ciencias Biomédicas (ICBM)

Jan 2016 – Feb 2016 Santiago, Chile

Development of cancer detection method based on Gene expression.

  • Technologies used: R

Recent Posts

Conic Optimization on Julia

Here I will describe a bit about conic programming on Julia based on Juan Pablo Vielma’s JuliaCon 2020 talk and JuMP devs Tutorials. We will begin by defining what is a cone and how to model them on JuMP together with some simple examples, by the end we will solve an mixed - integer conic problem of avoiding obstacles by following a polynomial trajectory.

Scientific Machine Learning on Julia

Here is what I’ve learned from the WorkShop Doing Scientific Machine Learning (SciML) With Julia from Chris Rackauckas. There is also an MIT course and Workshop exercises (with solutions) by the same author about this subject that I’ve been checking out and strongly recomend.

Learn Julia via epidemic modelling

An overview of what I’ve learned from the workshop