Paula Branco

About Me

I'm a PhD student in MAPi Doctoral Programme at the Department of Computer Science of the Faculty of Sciences - University of Porto, Portugal.

I have a degree in Mathematics (Educational Branch), a Specialization in the Master's degree course in Mathematics for School Teachers and a Masters degree in Computer Science (Specialization in Data Mining and Advanced Data Processing). All from the Faculty of Sciences, University of Porto.

In my Master thesis I have worked in the use of re-sampling approaches for regression tasks under imbalanced domains. My supervisor was Prof. Luís Torgo and my co-supervisor was Prof. Rita Ribeiro.

Currently I'm a PhD student in the Doctoral Programme in Computer Science of the Universities of Minho, Aveiro, and Porto (MAPi joint programme). I'm working in Utility-based Learning under the supervision of Prof. Luis Torgo and Prof. Rita Ribeiro.

You can see my cv here.

Research

My main research interests are Machine Learning and Data Mining. In particular, I'm interested in cost-sensitive/utility-based learning, anomaly detection, fraud detection and rare extreme values forecasting.

I was awarded a PhD scholarship that is fully funded by FCT (Portuguese Foundation for Science and Technology).

I'm connected with LIAAD (Artificial Intelligence and Decision Support Laboratory), a unit of INESC TEC since 2013.

In november/december 2015 I was visiting the Department of Computer Science of the Waikato University in Hamilton, New Zealand.

Publications

Here is a list of my publications:

Journals:

Paula Branco, Luis Torgo and Rita Ribeiro (accepted, to appear). A Survey of Predictive Modeling on Imbalanced Domains. ACM Computing Surveys
Paula Branco, Rita P. Ribeiro, Luis Torgo: UBL: An R Package for Utility-Based Learning. ArXiv preprint arXiv:1604.08079 (2016).
Paula Branco, Luis Torgo, Rita P. Ribeiro: A Survey of Predictive Modelling under Imbalanced Distributions. ArXiv preprint arXiv:1505.01658 (2015).
Luis Torgo, Paula Branco, Rita P. Ribeiro, and Bernhard Pfahringer. Resampling strategies for regression. Expert Systems 32(3): 465-476 (2015).

International Conferences with Peer Reviewing:

Bruno Cavadas, Paula Branco, Sergio Pereira: Crime Prediction Using Regression and Resources Optimization. EPIA2015: 513-524 (2015).
Luis Torgo, Rita P Ribeiro, Bernhard Pfahringer, and Paula Branco. SMOTE for Regression. EPIA2013: 378-389 (2013).

Thesis:

Msc: Re-sampling Approaches for Regression Tasks under Imbalanced Domains(2014)

You can also see my DBLP publications, my Research Gate or my google Scholar profile.

UBL Package

UBL is an R package developed for Utility-based Learning. The package includes several approaches for dealing with problems with different costs/benefits across the target variable domain. This is a frequent issue in imbalanced domains, so in particular, the implemented approaches are also able to deal with this problem.

Click here to see a presentation of UBL package!

The package is available on GitHub and on CRAN.