Jordi Turmo holds a PhD in artificial intelligence since 2002. He is working at TALP Research Center at UPC and is being professor at the UPC since 1995.His research focuses on the field of Natural Language Processing and specially on Advanced and Adaptive Text Mining (adaptive information extraction, document clustering, question answering, sentiment analysis...) in standard and non-standard text. Currently, he is involved in learning models for mining clinical histories, written in Spanish and Catalan, of multimorbid patients from primary care.He has participated in European projects: Acquilex-II, EuroWordNet, NAMIC, MEANING, CHIL and XLike, being the local coordinator at TALP-LSI of CHIL project. He also has participated in Spanish projects: ITEM, BASURDE, PETRA, ALIADO, TEXTMESS, KNOW2 and SKATER, being the coordinator at UPC of the two latter.Currently, he is interested in learning models for mining clinical histories, written in Spanish and Catalan, of multimorbid patients from primary care. Regarding this domain, he has been the coordinator at UPC of GRAPHMED Spanish project, and of the currently active TADIAMED Spanish project. He is also participating in the European project INTERACT. Mainly since 2006, he also participates in different I+D projects with different Spanish enterprises.He has teached different undergraduate subjects since 1995 in three different schools and faculties of the UPC (School of Technical Industrial Engineers of Terrassa, School of Industrial Engineers of Barcelona and Computer Science Faculty), concretely basic programming, data structures and algorithms, and artificial intelligence. He also has teached postgraduate subjects of the PhD in artificial intelligence at UPC since 2003 (Advanced techiques for Natural Language Processing and Natural Language Processing for the massive processing of textual information) and the course of Statistical Natural Language Processing of the PhD in Data Mining and Knowledge Management at UPC since 2011.He has been advisor of 4 PhD thesis related to Unsupervised learning for Relation Detection, Oral Question Answering, Entity Linking and Coreference Resolution in text.Nowadays, he is advising a PhD thesis related to Entity Linking.He is interested in the research and also in providing his expertise to the enterprise.Specialties: Natural Language Engineering, Adaptive Text Mining, Opinion Mining, Information Extraction, Question Answering, Document Clustering