R&D Software Engineer, Information Extraction Expert
Rafael

Rafa have a graduate degree in Computer Science Engineering from the University of Seville and a MSc in Linguistic Technologies and Data Mining from UNED. Ever since he started out to work, he has always been very interested not only in Software Engineering and Development, but also in applied research. He considers himself an enthusiast of anything related to Semantic Technologies, Machine Learning, Natural Language Processing, Text Mining and Heterogeneous Data Sources Integration.
Currently, his research is focused on Named Entities Disambiguation against Semantic Knowledge Bases like DBpedia or Wikipedia.

As Software Engineer, Rafa has always been working in highly innovative environments, both as a developer and as a researcher. When he faces a problem, he tries to divide it in two stages: find a state-of-the-art solution and code it. To date, his work has been mainly related to Semantic Technologies, NLP and Machine Learning for Automatic Document Processing, gaining experience with many tools like Lucene, Solr, GATE, OpenNLP, Apache Mahout, WEKA, Scikit-learn, Spark, Hadoop and many others.
He’s also an Apache Software Foundation committer, currently contributing to Apache Stanbol and Apache ManifoldCF.

Specialties : (Semantic) Search Engines, Natural Language Processing
Open Source : Apache Stanbol committer, Apache ManifoldCF committer
Current Research Topics : Entity disambiguation

Conference Sessions

– “Structuring Medical Records with Apache Stanbol” – Apachecon, Nov 2016 @Seville