Titles & Certifications

Master's Degree in Data Science

Sapienza University of Rome
Expected Graduation Date: July 2025

Bachelor's Degree in Physics

National Autonomous University of Mexico
Graduated August 2021

C1 English Level

Test of English as a Foreign Language (TOEFL iBT)
Issued February 2021

Additional Experience

Participant at the XII GEFENOL Summer School on Statistical Physics of Complex Systems

Rey Juan Carlos University of Madrid, Spain
1 July 2024 - 12 July 2024

Coming soon :)

Recent Projects

Reccomendation Engine for Netflix Users

Python project for the Algorithmic Methods of Data Science class for the MSc. in Data Science at the Sapienza University of Rome. The main purpose of the project was building a Recommendation Engine using Locally Sensitive Hashing and building a parallelized K-Means algorithm to cluster users based on their Netflix activity.

Pitch Prediction using MLB Data

Python project for the Fundamentals of Data Science class for the MSc. in Data Science at the Sapienza University of Rome. The main purpose of the project was to create and compare different Machine Learning classification models to predict baseball strikes using 2022 MLB pitching data.

Solving the Graph Coloring Problem with GNN's

Python project developed for the Advanced Machine Learning exam for the MSc. in Physics at the Sapienza University of Rome. The main purpose of the project was to recreate the results obtained in the article: Graph Coloring with Physics-Inspired Graph Neural Networks by Schuetz et al. (2022) by framing the Graph Coloring problem as a multi-class node classification problem and utilize an unsupervised training strategy based on the Statistical Physics Potts model.

Simulating an Epidemic on the GoT Universe

Python project developed for the Selected Topics of Thermodynamics and Statistical Physics class for the BSc. in Physics at the National Autonomous University of Mexico. The main purpose of the project is to to perform a basic Network Science analysis using the NetworkX package to the Game of Thrones networks of all TV seasons. It also includes a simple epidemic simulation on this network using the EoN package.