My research interests and work span Artificial Intelligence related areas such as:
Natural Language Processing:
Over the years, our research has addressed several issues regarding Natural-Language Processing (NLP) including adaptive natural-language interfaces, evolutionary shallow parsing techniques, natural-language dialogue systems for collaborative filtering, semantically-guided question-answering tasks, discourse information extraction, and multi-document summarization. Applications of our research include biomedical natural-language relations extraction, intelligent filtering for web-based interactive dialogue systems, patient literacy on biomedicine, call -center interaction systems, etc.
Funding: FONDECYT, FONDEF, CORFO, ECOS-CONICYT, TIC-AmSud, MIT-Chile Seeds Fund.
Text Mining and Knowledge Discovery:
Text Mining involves discovers novel patterns and hidden relationships from natural-language texts. Our recent work addresses several challenges and tasks in text data mining such as biomedical named-entity recognition, NLP for opinion mining, patterns discovery from specialized literature, semantically-guided lattices for association rules extraction, discovering cause-effect relationships, etc.
Funding: FONDECYT, FRIDA, ECOS-CONICYT, CORFO, FONDEF, Private Companies.
Machine Learning and Optimization:
Our research on machine learning has focused on novel methods for pattern recognition, artificial life evolution for internet agents,semantically-based classification, multi-objective optimization and learning, evolutionary methods for named-entity recognition, text categorization, etc. Current applications include fraud detection techniques, self-location in mobile agents, images classification, etc.
Funding: Private companies, CONICYT.
Agents and Multi-Agent Systems:
Past research on multi-agent systems focused on designing agents for intelligent search, robotic agents (i.e., RoboCup), behavior-based systems and autlomated multi-party negotiation, etc.
Funding: EXPLORA/CONICYT, Universidad de Concepción.