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.

Researchers

Avatar

Camila Marcuello

Research Engineer / MSc in Data Science

Machine Learning, Scheduling, Optimization

Avatar

Constanza Lorca

Research Engineer

Avatar

Alfredo de Rodt

Research Engineer

Prescriptive Analytics, Models Deployment, Explainable AI

Graduate Students

Avatar

César Cerda

MSc Student, Industrial Engineering and Operations Research

Optimization

Avatar

Andrés Lagos

MSc Student, Industrial Engineering and Operations Research

Machine learning, Algorithms, Renewable energy sources

Principal Investigator

Avatar

Rodrigo A. Carrasco

Associate Professor & the UC Data Science Initiative Director

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

Projects

Current research projects and grants

One of our aims is to connect theory and practice in our research. These are the current projects in which we are involved, and that allows us to connect the two. In these projects, we are using combinatorial optimization and stochastic modeling techniques to develop decision support tools in various settings. A full list is available here.

Operations Research Tools Applied to Scheduling in 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.

Predictive Maintenance

Developing tools for fault detection and diagnosis, in order to construct predictive maintenance systems.

Publications

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

Search for relevant content by filtering publications.
(2022). A RUL Estimation System from Clustered Run-to-Failure Degradation Signals. Sensors.

PDF Project DOI

(2022). Dealing with Uncertain Surgery Times in Operating Room Scheduling. European Journal of Operational Research.

PDF DOI

(2021). Using smartphone photographs of the Moon to acquaint students with non-Euclidean geometry. American Journal of Physics.

PDF DOI arXiv GitHub

(2020). Slow Degradation Fault Detection in a Harsh Environment. IEEE Access.

PDF Project DOI

(2020). Optimal decisions for salvage logging after wildfires. Omega THe International Journal of Management Science.

PDF 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.

Opportunities and challenges of generative AI

In this webcast, we share ideas and insights with Maria Francisca Yañez (Microsoft) and Patricio Cofre (EY) on the Opportunities and challenges we see with the new tools in generative AI.

Pauta de Negocios

In this short interview (in Spanish), we talk about the importance of correctly managing data within organizations and the value it can generate.

CNN Divergentes

In this program (in Spanish), we talk about how algorithms affect our lives and why we must be cautious during their design and implementation.

Interview at Radio Guayacán

In this interview (in Spanish), we talk about the importance of data for decision making.

It takes a village…

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

Collaborators

Avatar

Anthony D. Cho Lo

PhD in Industrial Engineering and Operations Research

Avatar

Gonzalo Ruz

Universidad Adolfo Ibáñez

Avatar

Macarena Azar

MSc in Engineering

Avatar

Susana Mondschein

Universidad de Chile

Avatar

Felipe Asenjo

Universidad Adolfo Ibáñez

Avatar

Hugo Caerols

Universidad Adolfo Ibáñez

Avatar

Eduardo Moreno

Universidad Adolfo Ibáñez

Avatar

Javiera Barrera

Universidad Adolfo Ibáñez

Avatar

José Luis Ortiz

ALMA Observatory

Avatar

Felipe Contreras

BSc in Industrial Engineering

Avatar

Gianluca Baselli

BSc in Industrial Engineering

Avatar

Magdalena Marín

BSc in Industrial Engineering

Avatar

Matías Lillo

BSc in Industrial Engineering

Avatar

Carlos Silva

Universidad Adolfo Ibáñez

Avatar

Francisco Jara

Universidad de Santiago de Chile

Avatar

Jocelyn Olivari

Universidad Adolfo Ibáñez

Avatar

Tito Homem de Mello

Universidad Adolfo Ibáñez

Avatar

David Rojas

Universidad de Chile / Instituto de Neurocirugía

Avatar

Gianpiero Canessa

KTH Royal Institute of Technology

Avatar

Ignacio Toledo

ALMA Observatory

Avatar

Sergio Martin

ALMA Observatory

Avatar

Cliff Stein

Columbia University

Avatar

Garud Iyengar

Columbia University

Avatar

José Verschae

Pontificia Universidad Católica de Chile

Avatar

Kirk Pruhs

University of Pittsburgh

Avatar

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