Ovidia Martínez Sánchez graduated with a Bachelor's degree in English Studies from the University of Alicante in 2021. The following year, she obtained a Master's degree in English and Spanish for Specific Purposes from the same institution. Her Master’s thesis, entitled La alfabetización en salud: un análisis del discurso de la reproducción asistida en páginas web, received the Segundo Premio en la categoría de Trabajos de Fin de Máster de los Premios de Investigación para Trabajos Fin de Grado y Máster en Materia de Transparencia, Acceso a la Información Pública, Buen Gobierno, Datos Abiertos e Integridad Institucional 2022, as well as the Accésit de los Premios Adam Kilgarriff 2023 from the University of Malaga. In 2024, she obtained a second Master’s degree in Medical and Healthcare Translation from Jaume I University. She has undertaken numerous specialist courses and postgraduate programmes, including the Expert in Natural Language Processing qualification awarded by the University of Alicante in 2025. She is currently a PhD candidate in Applied Linguistics at the University of Alicante.

Her research interests lie in computational linguistics, terminology, and the language of medicine. She has presented papers at numerous academic conferences and completed research placements abroad. In June 2024, she attended the Corpus Linguistics for the Analysis of Language, Discourse and Society summer school at Lancaster University. The summer school focused on advanced corpus-based methodologies for analysing discourse and its social dimension. She has also published in specialist journals and is an active member of the Professional and Academic Spanish (EPA) research group at the University of Alicante.

Professionally, she works as a research support technician on the research project "Neotermed4All: Terminología y comunicación biomédica para la inclusión y digitalización en salud" at the University of Alicante. Her research tasks include corpus design, compilation and annotation, terminological file extraction, and text reformulation to improve readability.

Her doctoral research in Applied Linguistics lies at the intersection of Corpus Linguistics and Natural Language Processing, focusing on text simplification in the medical field. The project involves compiling and TEI-annotating an anonymised corpus of Spanish medical reports. The aim is to evaluate strategies such as terminology reduction, controlled reformulation, and structural segmentation, using quantitative, corpus-based methods and current natural language processing (NLP) techniques. The research incorporates automatic evaluation and user-centred validation to improve the accessibility of clinical documentation from a gender-informed perspective. The project also aims to provide a reproducible resource for the automatic simplification of medical texts in Spanish.