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M.Sc

Universidad de Chile

Applied Mathematics

• Advanced Machine Learning
• Stochastic Simulatio
• Probability and Statistics in the Analysis of Data

Minor

Universidad de Chile

Computer Science

• Databases
• Algorithms and Data Structures
• Design and Programming Methodologies
• Software Engineering

B.Sc

Universidad de Chile

Mathematical Engineering

• Deep Learning
• Stochastic Calculus
• Nonlinear Optimization

Research Assistant

National Center for Artificial Intelligence (CENIA)

Developed a satellite image processing pipeline to analyze the evolution of wildfires in Chile, optimizing its efficiency and scalability.

• Analyzed wildfire data in Chile, extracting key metrics for segmentation.
• Automated the download and preprocessing of satellite images, improving data flow efficiency.
• Optimized queries in Google Earth Engine, accelerating them by 100x.
• Contributed improvements to the geetools library, benefiting the geospatial community.
• Stacks: Google Earth Engine | geopandas | geetools | scikit-learn

Research Assistant

Copenhagen Business School (CBS)

Researched and proposed new applications of the Bayesian Wasserstein Barycenter in the context of fairness models.

• Stacks: Fairness Models | Research | Wasserstein Barycenters

Master's Thesis Student

Center for Mathematical Modeling (CMM)

Calculated the Bayesian Wasserstein Barycenter (BWB) on a dataset of images using the Stochastic Gradient Descent algorithm on the Wasserstein space (WSGD).

• Implemented the WSGD algorithm abstractly, enabling its use by other researchers.
• Developed Wasserstein Generative Adversarial Networks (WGAN), optimizing training speed by a factor of 3x.
• Extended the WGAN architecture by incorporating an Autoencoder (AE), enabling a projector over the image manifold.
• Approximated the posterior distribution using GANs as the prior distribution, obtaining samples through the Markov Chain Monte Carlo (MCMC) algorithm.
• Developed a library to process and clean the Quick, Draw! dataset, implementing clustering algorithms to improve dataset quality.
• Stacks: PyTorch | WGAN | Autoencoders | MCMC | NUTS | Scikit-learn | Clustering | UMAP | TensorBoard

Freelance

Analysis of the Correlation between Inclusive Teaching Methodologies and Academic Performance of Primary Education Students

Conducted a statistical analysis to study the correlation between inclusive teaching methodologies and academic performance in primary education students.

• Used data analysis and visualization techniques to present results clearly.
• Applied statistical techniques to identify key patterns between teaching methodologies and academic performance.
• Performed categorical-numeric correlation analysis and hypothesis testing to validate the results.
• Developed a logistic regression model to predict academic performance.
• Stacks: Statistics | Hypothesis Testing | Logistic Regression | Pandas | Scikit-learn

Research Assistant

Center for Mathematical Modeling (CMM)

Performed feature engineering on seismic data and applied the Hawkes process for spatiotemporal probabilistic prediction of rock bursts.

• Developed processes to transform raw seismic data into relevant features, necessary for use in predictive models.
• Implemented the Hawkes process for spatiotemporal probabilistic predictions of rock bursts.
• Stacks: Stochastic Processes | Hawkes Processes | Feature Engineering

Data Scientist

Voyager Health

Predicted the INR index in patients undergoing oral anticoagulant treatment.

• Performed statistical analysis of INR time series, identifying key patterns.
• Implemented recurrent neural networks in TensorFlow and Keras, optimizing the training workflow.
• Stacks: Time Series | Recurrent Neural Networks | TensorFlow | Keras | Statistics

Freelance

Internet Service Allocation in Vulnerable Communities

Developed an optimization model to allocate Internet services in vulnerable communities.

• Formulated an optimal transport optimization model with capacity and demand constraints.
• Stacks: Optimization | Operations Research | Mathematical Programming | Python | PuLP

Data Scientist

SimpliRoute

Developed algorithms for anomaly detection in georeferenced data and service time analysis.

• Implemented clustering methods to identify anomalous georeferenced data, improving data quality.
• Developed an advanced system for detecting service times, enhancing logistics planning.
• Deployed key statistics for strategic analysis and decision-making.
• Stacks: Machine Learning | Clustering | Geospatial Analysis | Python | Scikit-learn | Pandas

R&D Engineer and Researcher Intern

SARCAN

Developed optimization models to improve route planning and efficiency in interurban transportation.

• Designed an action plan to enhance transportation operational efficiency. This plan is still being implemented today.
• Implemented optimization models to improve route planning.
• Stacks: Optimization | Operations Research | Mathematical Programming | Python | PuLP

Mentor in the AI Workshop for Students with Scratch

CONICYT

Taught students to understand, build, and use a Naive Bayes classifier in Scratch.

Mentor at Arduino Quest: Niñas PRO

Millennium Institute for Data Fundamentals (IMFD)

Guided students in developing an Arduino project.

• Participated in the 2020 and 2023 workshops.

Academic Team

Mathematics Championship (CMAT)

Prepared questions, graded exams, and answered inquiries during the competition.