About
Egoitz Laparra is a Researcher and Adjunct Instructor at the University of Arizona's College of Information Science since 2017. His work focuses on advancing natural language processing (NLP) methods for analyzing human language in medical and environmental domains. He specializes in machine/deep learning techniques for tasks like domain adaptation, information extraction, and semantic parsing.
Research Interests:
- Natural Language Processing (NLP) with emphasis on medical and environmental applications
- Machine learning and deep learning methodologies
- Domain adaptation and transfer learning in clinical and policy texts
- Geographical ontology development and toponym resolution
- Lexical resources like WordNet and predicate matrices
Publications highlight innovations in NLP for environmental policy analysis, clinical text mining, and cross-lingual semantic interoperability. His recent work addresses challenges in metadata extraction from environmental impact statements and improving geolocation entity recognition through deep learning. Collaborations include the NewsReader project for cross-lingual news analysis.
Laparra contributes to open-source projects like Eidos and INDRA, which transform free text into causal models. He maintains active involvement in international NLP competitions (e.g., SemEval tasks) and develops tools like Taxonomy Builder for knowledge organization.
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