Selected work
Research & applied projects
Research and applied initiatives where machine learning, optimization, and analytics support decisions in complex real-world settings.
- Fair and Explainable Machine Learning for Kidney Transplant Survival Prediction (2026-2029)
As PI, I develop fair, interpretable, and accurate machine learning survival models for kidney transplantation. This project focuses on competing risks and evaluates models such as optimal survival trees, survival SVMs, and deep learning architectures using the UNOS database, with the aim of supporting clinically relevant and policy-aligned transplant decisions.
- Improving Effectiveness and Equity in Kidney Exchange Programs (2024)
As a research assistant, I have been involved in designing and implementing survival models for kidney transplants.
- Dream Team Generator for School Cohesion (2022)
Led the development of a Dream Team Generator, funded by CORFO, aimed at enhancing cohesion within schools. The project involved creating an algorithm that optimizes team composition by considering a variety of social and academic metrics. This tool has been successfully implemented to foster collaboration and improve the sense of community among students and staff, contributing to a more inclusive and supportive school environment.
- A Novel Machine Learning Pipeline for Variable Star Classification (2018-2022)
As a research assistant, I developed a machine learning pipeline that classifies variable stars. This pipelines were designed mainly to handle the challenges of data shift in astronomical observations.
- Early Warning System for Chilean Tomato Paste Industry (2014-2016)
As a research assistant, I collaborated on the development of an early warning system to control Alternaria alternata in the Chilean tomato paste industry. This system, funded by FIA, utilized non-destructive technologies to predict and mitigate the impact of agricultural pests, significantly reducing losses in the industry.
- Web Optimization Decision Support System for Maule Region Food Processing Plants (2014-2016)
Directed a project that developed a web-based optimization decision support system for operations planning in food processing plants in the Maule region. Funded by GORE Maule, the system improved operational efficiency and decision-making in the food processing industry.
- On a Class of Robust Combinatorial Optimization Problems (2012-2013)
As a research assistant, In this project I was focused on addressing the Min-Max Regret Path Problem, Min-Max Regret Tree Problem, and Interdiction Problems on paths. The research aimed to develop robust solutions that minimize the worst-case regret under uncertainty, with applications in network design and security.