Welcome to our Research Webpage

Operations Research, Prescriptive Analytics, and Systems Engineering.

Our Research

What we do…

We are interested in harnessing the power of operations research, predictive analytics, and prescriptive analytics methodologies, to develop decision support tools for applied problems.

Currently, our research has focused on two main methodological areas:

Combinatorial algorithms
Stochastic optimization and Uncertainty modeling

We work in combining both areas, focused on applications, to make robust decision support systems. The applications we are looking into right now are energy management and astronomical observatory operations. They look far away from each other, but similar techniques can help significantly improve the processes if both settings. And both have large amounts of data that we can use to train, test, and validate our developments.

Look into our Projects section for more information on our current projects, and Contact us if you want to participate in some of them.

Research Team

Current researchers and students working in our research group.

Doctoral Students

Andrés Catlán

Ph.D. Student, Industrial Engineering and Operations Research

Machine learning, Optimization, Maintenance

Raúl Araneda

Ph.D. Student, Engineering and Sciences with the Industry

Optimization, Healtchare

Research Engineers

Luis Arias

Research Engineer / B.S. in Engineering

Optimization, Operations Research

Camila Marcuello

Research Engineer / M.S. in Data Science

Machine Learning, Scheduling, Optimization

Sol Covacich

B.S. in Engineering

Computer Science, Data Science

Graduate Students

Diego San Martín

M.S. Student, Industrial Engineering and Operations Research

Optimization, Prescriptive Analytics

Rodrigo Munizaga

M.S. Student, Industrial Engineering and Operations Research

Machine learning, Prescriptive Analytics

Andrés Lagos

M.S. Student, Industrial Engineering and Operations Research

Machine learning, Algorithms, Renewable energy sources

Undergraduate Students

Tomás Couso

B.S. in Engineering

Machine learning, Satellite Image Processing

Matilde Valdés

B.S. in Engineering

Optimization, Operations Research

Pedro Zavala

B.S. in Engineering

Computer Science, Data Science

Principal Investigator

Rodrigo A. Carrasco

Associate Professor & the UC Data Science Initiative Director

Combining Predictive and Prescriptive Analytics, Combinatorial Algorithms, Algorithm Design & Analysis

Featured Publications

Some of the recent publications we want to highlight.

A Fine-Tuned BERT-Based Model for Individual Log Anomaly Detection in Operational Monitoring at Paranal Observatory

In operational environments such as astronomical observatories, continuous monitoring of system logs is critical yet challenging due to …

Andres Catalan, Rodrigo A. Carrasco, Gonzalo Ruz, Juan Pablo Gil

PDF Project Project Project DOI

Strategies for the Management and Prioritization of Oncology Waiting Lists in the Chilean Public Health System

This chapter presents strategies to improve the management and prioritization of oncology waiting lists in the Chilean public health …

Rodrigo A. Carrasco, Jocelyn Dunstan, José Peña

PDF Project Chapter Book

Strategy for the Implementation of a FAIR Data Policy in Chile

This report presents Chile’s national strategy for implementing the FAIR data principles—Findable, Accessible, Interoperable, and …

Isabel Abedrapo, Rodrigo A. Carrasco, Alfredo Catalán, Ignacia Díaz, Paul Escapil-Inchauspe, Ricardo Hartley, Ana Lucía Keim, Maximiliano Koebl, Natalie Meyers, Sebastián Quiroz, Ángela Paredes, Macarena Rivera, Rodrigo Roa

PDF DOI

Enhanced Detection of Human-Driven Forest Alterations using Echo State Networks

Forest monitoring is crucial for understanding ecosystem dynamics, detecting changes, and implementing effective conservation …

Tomas Couso, Paula Aguirre, Rodrigo A. Carrasco, Javier Lopatin

PDF Project Conference

Uncertainty estimation through quantile forest for prescriptive scheduling of data processing at ALMA

The Atacama Large Millimeter/submillimeter Array (ALMA) is a prominent astronomical observatory known for its detailed imaging …

Rodrigo A. Carrasco, Luis Aburto, Jorge Garcia, Alfredo De Rodt, Gianfranco Speroni

PDF Project DOI

See all publications

Research Lines & Projects

Current research lines and grants

Our research is driven by the goal of bridging theory and practice, developing both predictive and prescriptive tools through mathematical optimization. These ongoing projects exemplify our approach, and research lines, where we leverage combinatorial optimization and stochastic modeling techniques to create decision support systems across diverse real-world applications.

You can find a list of our grants here, and a full list of current and past projects is available here.

PLASMA: Analytical Platform for Maintenance Systems

Developing a cloud-based analytical platform to optimize predictive and prescriptive maintenance across industrial systems.

Development of Oncology Waiting List Prioritization Strategies

We are studying data-driven prioritization models that can help hospitals manage their oncology waiting lists with application in the South Eastern Metropolitan Health Service

Resource cost-aware scheduling problems under uncertainty

FONDECYT Regular project. Developing resource cost-aware scheduling solutions to optimize performance under uncertainty, with applications in astronomy and other industries.

Operations Research Tools Applied to Observatory Operations

Using operations research methodologies, we are developing new tools for observatory operations.

ClimateDL: Forecasting of extreme temperature events

Using deep learning spatial-temporal graph models for seasonal forecasting of extreme temperature events.

GEMS: variable-Generation Energy Management with Storage

We are combining machine learning and stochastic optimization tools to develop optimal energy management systems for fotovoltaic generation with storage.

Prescriptive Maintenance

Developing ML and decision support tools for predictive and prescriptive maintenance.

Publications

All of our group’s publications; easy to sort and cite.

Search for relevant content by filtering publications.

Andres Catalan, Rodrigo A. Carrasco, Gonzalo Ruz, Juan Pablo Gil (2025). A Fine-Tuned BERT-Based Model for Individual Log Anomaly Detection in Operational Monitoring at Paranal Observatory. IEEE Access.

PDF Project Project Project DOI

Rodrigo A. Carrasco, Jocelyn Dunstan, José Peña (2025). Strategies for the Management and Prioritization of Oncology Waiting Lists in the Chilean Public Health System. Propuestas para Chile 2024.

PDF Project Chapter Book

Isabel Abedrapo, Rodrigo A. Carrasco, Alfredo Catalán, Ignacia Díaz, Paul Escapil-Inchauspe, Ricardo Hartley, Ana Lucía Keim, Maximiliano Koebl, Natalie Meyers, Sebastián Quiroz, Ángela Paredes, Macarena Rivera, Rodrigo Roa (2025). Strategy for the Implementation of a FAIR Data Policy in Chile. Public Policy Report.

PDF DOI

Tomas Couso, Paula Aguirre, Rodrigo A. Carrasco, Javier Lopatin (2024). Enhanced Detection of Human-Driven Forest Alterations using Echo State Networks. NeurIPS Workshop on Tackling Climate Change with Machine Learning.

PDF Project Conference

Rodrigo A. Carrasco, Luis Aburto, Jorge Garcia, Alfredo De Rodt, Gianfranco Speroni (2024). Uncertainty estimation through quantile forest for prescriptive scheduling of data processing at ALMA. Observatory Operations: Strategies, Processes, and Systems X.

PDF Project DOI

See all publications

Recent Talks

Conferences and science communication

These are some of the recent talks and conferences in which we have participated. A full list is available here.

Joining prediction and optimization: prescriptive scenario generation for energy management with storage

In this presentation we sumarized the work we’ve done in connecting predictions and prescription for models and algorithms in energy management with uncertain generation and storage.

Mar 25, 2025 8:30 AM — 9:00 AM Santiago, Chile

Rodrigo A. Carrasco

Project webpage

When Time Is Life: Innovation for Oncology Waitlists in Chile

The article discusses how data-driven innovation can transform oncology waitlist management in Chile, reducing delays and improving patient access to timely care. It highlights key strategies, including digitalization, automation, and optimization, to enhance efficiency and equity in the healthcare system.

Mar 12, 2025 8:30 AM — 9:00 AM España

Rodrigo A. Carrasco, José Peña

Project webpage