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.

Researchers

Constanza Lorca

Research Engineer

Helena García

Research Engineer / MSc in Engineering

Combinatorial Problems, Machine Learning, Prescriptive Analytics

Graduate Students

Camila Marcuello

MSc Student, Data Science

Machine Learning, Scheduling, Optimization

Paula Oyarzún

MSc Student, Industrial Engineering and Operations Research

Scheduling, Optimization

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 RUL Estimation System from Clustered Run-to-Failure Degradation Signals

The prognostics and health management disciplines provide an efficient solution to improve a system’s durability, taking advantage of …

Anthony Cho, Rodrigo A. Carrasco, Gonzalo Ruz

PDF Project DOI

Improving prescriptive maintenance by incorporating post-prognostic information through chance constraints

Maintenance is one of the critical areas in operations in which a careful balance between preventive costs and the effect of failures …

Anthony Cho, Rodrigo A. Carrasco, Gonzalo Ruz

PDF Project DOI GitHub

Dealing with Uncertain Surgery Times in Operating Room Scheduling

The operating theater is one of the most expensive units in the hospital, representing up to 40% of the total expenses. Because of its …

Rodrigo A. Carrasco, Susana Mondschein, Macarena Azar

PDF DOI

Using smartphone photographs of the Moon to acquaint students with non-Euclidean geometry

Although they are sometimes considered problematic to grasp by students, the concepts behind non-Euclidean geometry can be taught using …

Hugo Caerols, Rodrigo A. Carrasco, Felipe Asenjo

PDF DOI arXiv GitHub

Slow Degradation Fault Detection in a Harsh Environment

The ever increasing challenges posed by the science projects in astronomy have skyrocketed the complexity of the new generation …

Anthony Cho, Rodrigo A. Carrasco, Gonzalo Ruz, José L. Ortiz

PDF Project DOI

Optimal decisions for salvage logging after wildfires

Strategic, tactical, and operational harvesting plans for the forestry and logging industry have been widely studied for more than 60 …

Gianluca Baselli, Felipe Contreras, Matías Lillo, Magdalena Marin, Rodrigo A. Carrasco

PDF DOI

See all publications

Projects

Current applied research projects

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.

Operations Research Tools Applied to Scheduling in Observatory Operations

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

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.

Anthony Cho, Rodrigo A. Carrasco, Gonzalo Ruz (2022). A RUL Estimation System from Clustered Run-to-Failure Degradation Signals. Sensors.

PDF Project DOI

Anthony Cho, Rodrigo A. Carrasco, Gonzalo Ruz (2022). Improving prescriptive maintenance by incorporating post-prognostic information through chance constraints. IEEE Access.

PDF Project DOI GitHub

Rodrigo A. Carrasco, Susana Mondschein, Macarena Azar (2022). Dealing with Uncertain Surgery Times in Operating Room Scheduling. European Journal of Operational Research.

PDF DOI

Hugo Caerols, Rodrigo A. Carrasco, Felipe Asenjo (2021). Using smartphone photographs of the Moon to acquaint students with non-Euclidean geometry. American Journal of Physics.

PDF DOI arXiv GitHub

Rodrigo A. Carrasco (2021). Equipo, sistema y método para administrar óptimamente la energía en una red de uso domiciliario e industrial. CL00938-2019.

PDF Project

Anthony Cho, Rodrigo A. Carrasco, Gonzalo Ruz, José L. Ortiz (2020). Slow Degradation Fault Detection in a Harsh Environment. IEEE Access.

PDF Project DOI

Gianluca Baselli, Felipe Contreras, Matías Lillo, Magdalena Marin, Rodrigo A. Carrasco (2020). Optimal decisions for salvage logging after wildfires. Omega THe International Journal of Management Science.

PDF DOI

See all publications