Primarily my research lies at NLP

My research lies at the intersection of Natural Language Processing (NLP), Artificial Intelligence (AI), and Machine Learning (ML), with a particular focus on understanding and modeling semantic similarity, that is, how machines interpret the meaning of words, phrases, and sentences. As a member of the iXa research unit and HiTZ Center for Language Technology at the University of the Basque Country (UPV/EHU)), I work to advance the field of human language technologies with the aim of building more intelligent, ethical, and linguistically aware systems.

Plenty of work at the Semantic Textual Similarity (STS) domain

My academic journey began with a deep curiosity about how language works, which evolved into a master’s degree and a Ph.D. in NLP. Since then, my research has been centered on lexical and semantic similarity, text understanding, and meaning representation, which are core challenges in making machines truly comprehend human language. I’ve applied these concepts to tasks such as paraphrase detection, sentence alignment, semantic textual similarity (STS), and natural language inference (NLI).

Recent work

Much of my recent work involves designing and evaluating deep learning models for language representation using frameworks such as PyTorch, TensorFlow, and Keras. I have a strong interest in transfer learning and pre-trained language models like BERT-like, Llama and GPT, especially in how they can be adapted to low-resource languages such as Basque or applied to domain-specific problems.

Beyond theoretical development, I believe research should contribute to solving real-world problems. I’ve collaborated on applied NLP projects in fields such as transportation, logistics, and industry 4.0, where natural language interfaces and semantic search improve user experience and decision-making.

Open-source tools

I also maintain a strong interest in open-source NLP tools and reproducible research, regularly publishing code and resources to support the broader research community.

Past, present and future work

With over 45 peer-reviewed publications and nearly 3,000 citations, my work has been presented at leading conferences and journals. I also serve as a reviewer for academic journals and conference tracks in NLP, and actively mentor students and junior researchers in the field.

Looking forward, I aim to deepen my research into multilingual NLP, explainable AI, and neural approaches to improve textual understanding, while continuing to explore the intersection between linguistics, data science, and education. I am particularly passionate about leveraging NLP to create more accessible, equitable, and intelligent information systems that understand, and not just process human language.

In every project, I seek to combine linguistic insight, computational power, and ethical awareness to push the boundaries of what language technology can achieve.