I am a Master’s student at the University of Chile, interested in Data Science, Machine Learning and Software Engineering. I am developing my Master’s thesis on the Interpretability of Graph Neural Networks using Logic. I have a strong interest in Recommendation Systems and applied Machine Learning.

My experience consists mostly of researching uses of Machine Learning on source code and implementing various prototypes for freelance and research projects. This includes feature and data engineering, software development and results reporting. I also have experience in teaching as a TA for several courses in University, ranging from advanced programming methodology classes to data mining and deep learning.

When not in front of my computer I am reading, studying Japanese, Kanji or building mechanical keyboards. I also love rhythm games.


  • Machine Learning
  • Source Code Representation
  • Structured Representation Learning
  • Reinforcement Learning
  • Recommendation Systems


  • B.Eng.Sc. in Computer Science, 2018

    University of Chile



Research Assistant

Intelligent Software Construction Laboratory (ISCLab)

Jan 2017 – Present Santiago, Chile
Research on applying machine learning to source code.

Data Science Intern

We Techs

Jul 2018 – Dec 2018 Santiago, Chile
Was part of a team in charge of migrating the company’s services from a relational schema to a ELK stack, then adding intelligence to the company’s data. Specifically in charge of the ElasticSearch configuration and data analytics. Data processing and apply machine learning algorithms to improve company’s control protocols.

Research Intern

Inria Chile

Jul 2017 – Jul 2017 Santiago, Chile
Within the context of AI-assisted educational video game with ethic and moral themes:

  • Compile bibliography related to automatic consistent narrative generation, and adapt and implement several techniques of narrative generation.
  • Design of a proposal for the integration of automatic generated ethical and moral conflicts, through related narratives, to the video game.


NIC Chile Research Labs

Dec 2016 – Jan 2017 Santiago, Chile
Improve task efficiency inside the lab:

  • Install and configure HTC (High-throughput computing) software to automate tasks inside the laboratory.
  • Evaluate the installed software on several environments inside the laboratory to quantify the positive impact of using it.


CC5206 - Introduction to Data mining

Head Teaching Assistant

Spring 2019 – Fall 2020 (2 semesters) University of Chile
  • Coordination and management of Teaching Assistants and course activities.
  • Laboratory activity preparation.
  • Course covers Linear Models, Decision Trees, Clustering, Model Evaluation and standard Data Mining Pipelines.

CC6204 - Deep Learning

Teaching Assistant

Spring 2019 University of Chile
  • Office hours to assist students with their course projects.
  • Grading of homeworks and projects.
  • Course covers Basic Tensorial Calculus, Feedforward, Recurrent and Convolutional Neural Networks, Activation Functions, Losses and Theory.

CC3002 - Design and Programming Methodologies

Head Teaching Assistant

Fall 2017 – Spring 2019 (6 semesters) University of Chile
  • Recitation classes (theoretical and practical) and design of homework material.
  • Management of teaching aides for test, exam and homework grading.
  • Course covers Object Oriented Programming and Design Patterns, as well as design guidelines and Intermediate Java programming.

CC5114 - Neural Networks and Genetic Programming

Teaching Assistant

Spring 2018 – Spring 2019 (2 semesters) University of Chile
  • Office hours to assist students with their course projects.
  • Management of teaching aides for homework grading.
  • Course covers introductory Neural Networks, then changes to Evolutionary Algorithms, Neuroevolution (like NEAT), Genetic Algorithms and Genetic Programming.

CC66M - Evolutionary algorithms

Teaching Assistant

Spring 2019 University of Chile
Course required for the professional Artificial Intelligence diploma:

  • Homework design and grading.
  • Assist students in the laboratory sessions.
  • Course covers introductory Evolutionary and Genetic Algorithms. Also has an introduction to Reinforcement Learning using Q-learning.

Recent Publications

The Logical Expressiveness of Graph Neural Networks

The ability of graph neural networks (GNNs) for distinguishing nodes in graphs has been recently characterized in terms of the …

Logical Expressiveness of Graph Neural Networks

The ability of graph neural networks (GNNs) for distinguishing nodes in graphs has been recently characterized in terms of the …


Language skills

  • Spanish: Native
  • English: Fluent
  • Japanese: Fluent/Business (JLPT N2 )


Python, Java, Pytorch, Scikit Learn, Git, Linux, Django



  • Member of the Academic Evaluation Committee, 2018 - Present


  • External Reviewer, SANER’2019 (IEEE International Conference on Software Analysis, Evolution, and Reengineering) ERA Track


  • Co-Instructor at the Artificial Intelligence Workshop, organized by OpenBeauchef. May, Aug 2019.

Recent & Upcoming Talks

Advanced Python: the most pretentious title you will hear today (In Spanish)

Aprende tópicos avanzados de Python como herencia multi-clase, super clases virtuales y metaclases.