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

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Andrés Catlán

Ph.D. Student, Industrial Engineering and Operations Research

Machine learning, Optimization, Maintenance

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Raúl Araneda

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

Optimization, Healtchare

Research Engineers

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Luis Arias

Research Engineer / B.S. in Engineering

Optimization, Operations Research

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Camila Marcuello

Research Engineer / M.S. in Data Science

Machine Learning, Scheduling, Optimization

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Sol Covacich

B.S. in Engineering

Computer Science, Data Science

Graduate Students

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Diego San Martín

M.S. Student, Industrial Engineering and Operations Research

Optimization, Prescriptive Analytics

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Rodrigo Munizaga

M.S. Student, Industrial Engineering and Operations Research

Machine learning, Prescriptive Analytics

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Andrés Lagos

M.S. Student, Industrial Engineering and Operations Research

Machine learning, Algorithms, Renewable energy sources

Undergraduate Students

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Tomás Couso

B.S. in Engineering

Machine learning, Satellite Image Processing

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Matilde Valdés

B.S. in Engineering

Optimization, Operations Research

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Pedro Zavala

B.S. in Engineering

Computer Science, Data Science

Principal Investigator

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Rodrigo A. Carrasco

Associate Professor & the UC Data Science Initiative Director

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

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.

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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.
(2025). Strategy for the Implementation of a FAIR Data Policy in Chile. Public Policy Report.

PDF DOI

(2024). Enhanced Detection of Human-Driven Forest Alterations using Echo State Networks. NeurIPS Workshop on Tackling Climate Change with Machine Learning.

PDF Project Conference

(2024). Uncertainty estimation through quantile forest for prescriptive scheduling of data processing at ALMA. Observatory Operations: Strategies, Processes, and Systems X.

PDF Project DOI

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.

13th International Conference on Mathematical Methods in Reliability

Our team participated in MMR 2025 with three talks showcasing recent advances in data-driven maintenance. The presentations covered applications in the airline industry, distributed systems, and the wine sector, highlighting our interdisciplinary approach to predictive modeling, anomaly detection, and operational optimization.

Advancing Research through Integrated Scientific and Operational Data Management and Governance

At PASC 2025, I presented our work on building a trusted and scalable data infrastructure to support the Regional Field Stations Network (RCER) at Universidad Católica. The talk introduced SAVIIA—a platform that integrates scientific and operational datasets across distributed field stations using structured governance, local orchestration tools, and cloud-based pipelines. By improving data reliability, accessibility, and integration, the initiative aims to empower researchers, foster interdisciplinary collaboration, and enhance reproducibility in field-based science.

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

In this presentation, I summarized our work on connecting prediction and prescription in energy management for residential microgrids, using stochastic optimization and machine learning to improve decision-making under uncertainty in systems with variable generation and storage.

When Time Is Life: Innovation for Oncology Waitlists in Chile

Opinion piece in El País exploring how data-driven innovation can improve oncology waitlist management in Chile through digitalization, automation, and optimization.

It takes a village…

These are some of the great collaborators we’ve had the chance of working with in our research.

Collaborators

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Andrés Catlán

Ph.D. Student, Industrial Engineering and Operations Research

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Gonzalo Ruz

Universidad Adolfo Ibáñez

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Juan Pablo Gil

European Southern Observatory - Paranal Observatory

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Alejandro Mac Cawley

Pontificia Universidad Católica de Chile

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Jocelyn Dunstan

Pontificia Universidad Católica de Chile

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José Peña

Physician at Servicio de Salud Metropolitano

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Javier Lopatin

Universidad Adolfo Ibáñez

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Paula Aguirre

Professor

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Anthony D. Cho Lo

Ph.D. in Industrial Engineering and Operations Research

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Margarita Castro

Pontificia Universidad Católica de Chile

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Alfredo de Rodt

Research Engineer

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Jorge García

ALMA Observatory

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Luis Aburto

Universidad Adolfo Ibáñez

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Ignacio Fuentes

Universidad de Chile

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Mauricio Galleguillos

Universidad Adolfo Ibáñez

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Susana Eyheramendy

Universidad Adolfo Ibáñez

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Macarena Azar

M.S. in Engineering

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Susana Mondschein

Universidad de Chile

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Felipe Asenjo

Universidad Adolfo Ibáñez

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Hugo Caerols

Universidad Adolfo Ibáñez

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Eduardo Moreno

Universidad Adolfo Ibáñez

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Javiera Barrera

Universidad Adolfo Ibáñez

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José Luis Ortiz

ALMA Observatory

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Felipe Contreras

B.S. in Industrial Engineering

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Gianluca Baselli

B.S. in Industrial Engineering

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Magdalena Marín

B.S. in Industrial Engineering

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Matías Lillo

B.S. in Industrial Engineering

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Carlos Silva

Universidad Adolfo Ibáñez

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Francisco Jara

Universidad de Santiago de Chile

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Jocelyn Olivari

Universidad Adolfo Ibáñez

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Tito Homem de Mello

Universidad Adolfo Ibáñez

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David Rojas

Universidad de Chile / Instituto de Neurocirugía

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Gianpiero Canessa

KTH Royal Institute of Technology

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Ignacio Toledo

ALMA Observatory

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Sergio Martin

ALMA Observatory

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Cliff Stein

Columbia University

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Garud Iyengar

Columbia University

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José Verschae

Pontificia Universidad Católica de Chile

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Kirk Pruhs

University of Pittsburgh

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Aldo Cipriano

Pontificia Universidad Católica de Chile

Contact

Interested in our work? Here is how to contact us.

  • +56 (2) 95504-4178
  • Av. Vicuña Mackenna 4860, Santiago, 7820436
  • Edificio Raúl Devés, Piso 3