My research interests are in the area of Machine Learning, focused on the field of inductive learning and its applications. Most of my work has been on the problem of clustering categorical data and, particularly, on conceptual clustering.
My main current interest (and the topic of my forthcoming dissertation) is feature selection in clustering, which is a topic that I consider of great interest but that has been largely neglected in the literature.
I have also worked in the problem of ordering effects in incremental clustering in joint work with Josep Roure, from EUPMT.
In addition, I am interested in Psychological models of categorization. My aim is not such ambitious as to build a model of human cognition, but I think that Cognitive Psychology can provide useful biases to design artificial learning systems and guidelines about human preferences.
From my work in the business intelligence industry, I have also developed a high interest in issues related to data mining such as data preparation, postprocessing and interpretation of results and visualization.
I am also doing joint work with Elena Gaudioso from the UNED in applying machine learning to web-based educational environments, particularly those aimed to collaborative learning. This includes not only building learning models for user modeling, adaptive navigation and profiling, but also solving problems such as data gathering and preprocessing, finding useful learning tasks and defining indicators of collaborative activity and student performance.