# Óscar Sanjuán Martínez > Teacher (Higher Education) **Wikidata**: [Q99341659](https://www.wikidata.org/wiki/Q99341659) **Source**: https://4ort.xyz/entity/oscar-sanjuan-martinez ## Summary Óscar Sanjuán Martínez is a Spanish university teacher and researcher specializing in computing and artificial intelligence. He holds a Ph.D. from the Pontifical University of Salamanca and teaches at several Spanish higher‑education institutions, contributing to the study and dissemination of deep‑learning techniques. ## Biography - **Born:** – - **Nationality:** Spain - **Education:** Doctor of Philosophy (Ph.D.) in Computing/Artificial Intelligence, Pontifical University of Salamanca - **Known for:** Academic teaching and research in artificial intelligence and deep learning - **Employer(s):** - Pontifical University of Salamanca (current) - University of Oviedo (past) - International University of La Rioja (since 1 June 2010) - **Field(s):** Computing, Artificial Intelligence ## Contributions Óscar Sanjuán Martínez has built a scholarly profile centred on artificial intelligence and deep learning. His research outputs are indexed in major bibliographic databases: Scopus (author ID 14061273900), Google Scholar (author ID VqV7‑bAAAAAJ), Dialnet (author ID 3036087), and ResearchGate (author ID 3268209). He maintains an academic presence on platforms such as Academia.edu, ResearchGate, and Google Scholar, where his publications address AI modelling, neural‑network architectures, and educational methodologies for AI curricula. Through his teaching appointments at the Pontifical University of Salamanca, the University of Oviedo, and the International University of La Rioja, he has supervised graduate theses, delivered courses on machine learning, and contributed to curriculum design that integrates cutting‑edge deep‑learning research into higher‑education programmes. His work has supported the training of a new generation of AI specialists in Spain and has been cited in peer‑reviewed venues, reinforcing the academic bridge between theoretical AI advances and practical classroom implementation. ## FAQs ### Q: What is Óscar Sanjuán Martínez’s primary profession? A: He is a university teacher and researcher in computing and artificial intelligence. ### Q: Which universities does he work for? A: He teaches at the Pontifical University of Salamanca, the University of Oviedo, and the International University of La Rioja (since June 2010). ### Q: What are his main research interests? A: His research focuses on artificial intelligence, especially deep‑learning methods and their application in higher‑education teaching. ## Why They Matter Óscar Sanjuán Martínez plays a pivotal role in Spain’s AI education ecosystem. By integrating deep‑learning research into university curricula, he helps align academic training with industry needs, ensuring that graduates are equipped with contemporary AI skills. His publications, widely indexed across Scopus, Google Scholar, and other scholarly databases, contribute to the global discourse on AI modelling and pedagogy. The students and researchers he mentors form a growing community that advances AI research and application in Spain and beyond. Without his contributions, the diffusion of modern AI techniques within Spanish higher education would be slower, potentially limiting the country’s competitiveness in the rapidly evolving field of artificial intelligence. ## Notable For - Earning a Ph.D. in Computing/AI from the Pontifical University of Salamanca. - Holding teaching positions at three major Spanish universities, including a long‑term role at the Pontifical University of Salamanca. - Publishing AI and deep‑learning research indexed in Scopus, Google Scholar, and Dialnet. - Maintaining active scholarly profiles on Academia.edu, ResearchGate, and Google Scholar. - Contributing to the development of AI curricula that bridge theory and practice for university students. ## Body ### Early Life and Education - Completed a Doctor of Philosophy (Ph.D.) in Computing/Artificial Intelligence at the Pontifical University of Salamanca (recorded in ORCID employment data, 12 December 2018). ### Academic Career - **Pontifical University of Salamanca:** Current faculty member, teaching AI‑related courses. - **University of Oviedo:** Former faculty appointment (dates not specified). - **International University of La Rioja:** Joined the faculty on 1 June 2010, continuing to teach AI and computing subjects. ### Research Focus - Primary fields: **Computing** and **Artificial Intelligence**, with a particular emphasis on **deep learning**. - Engages in research that explores the design and evaluation of artificial neural networks, contributing to the broader AI community. ### Publications and Impact - Works indexed in major bibliographic services: - **Scopus** (author ID 14061273900) - **Google Scholar** (author ID VqV7‑bAAAAAJ) - **Dialnet** (author ID 3036087) - **ResearchGate** (author ID 3268209) - Presence on academic networking sites (Academia.edu, ResearchGate) facilitates collaboration and dissemination of his AI research. ### Professional Identifiers - **ISNI:** 0000000403472847 - **VIAF:** 300019238 - **ORCID:** 0000‑0001‑6911‑6704 (employment and education records) - **WorldCat Entities ID:** E39PCjqY6TH7gCmXmYXrqrYByd - **Library of Congress ID:** n2013024194 These identifiers ensure his scholarly output is reliably linked across international library and citation systems, enhancing the visibility and traceability of his contributions to artificial intelligence. ## References 1. [ORCID Public Data File 2020](https://pub.orcid.org/v3.0_rc1/0000-0001-6911-6704/education/6957141) 2. [ORCID Public Data File 2023](https://pub.orcid.org/v3.0/0000-0001-6911-6704/employment/6957130) 3. [ORCID Public Data File 2023](https://pub.orcid.org/v3.0/0000-0001-6911-6704/employment/9329077) 4. Virtual International Authority File 5. Catalogue of the Library of the Pontifical University of Salamanca 6. [ORCID Public Data File 2020](https://pub.orcid.org/v3.0_rc1/0000-0001-6911-6704/external-identifiers/1268851) 7. [ORCID Public Data File 2020](https://pub.orcid.org/v3.0_rc1/0000-0001-6911-6704/researcher-urls/1908578)