The research focuses primarily on the study of intelligent systems with particular emphasis on adaptive and personalized communication environments as well as user behavior prediction systems. The field is generally broad and covers a wide range of applications, such as recommender systems, adaptive hypermedia and data journalism applications. More specifically, the work is focused on:

• Adaptation of content and services to improve the user interaction in communication environments through personalization techniques based on the influence of cognitive and emotional processes during the interaction of the user with the hypertext. Particular emphasis is placed on online education, game based learning and affective user interfaces.

• Recommender Systems based on the collection of large data derived from the traces and user interaction and the application of content-based or user-based filtering algorithms.

• The application of content analysis techniques, natural language processing, and artificial intelligence algorithms in journalism, political and journalistic discourse analysis and the study of user behavior during interaction with digital media. Particular emphasis is placed on research into the retrieval, processing and visualization of information and pattern recognition, hidden in a very large volume of data (dig data analysis), which are sometimes structured, semi-structured or even unstructured. Programming languages ??such as Python and R as well as artificial intelligence algorithms for classification, extraction and retrieval of patterns, natural language processing algorithms for retrieving opinions and emotional tendency of texts, are used to extract stories hidden in a very large volume of (possible user-generated) content.

Recent research work is described in the webpage of his research team working in the field of Computational Journalism.