Skip to main content

David Sánchez Ruenes

ICREA Acadèmia 2020

Universitat Rovira i Virgili · Engineering Sciences

David Sánchez Ruenes

David Sánchez Ruenes is a Full Professor at Universitat Rovira i Virgili, Tarragona. He obtained his Ph.D. in Computer Science in 2008 from the Polytechnic University of Catalonia.

He has participated in 11 European projects (one as Principal Investigator and one H2020 project as coordinator), 10 Spanish projects (2 as a PI) and 15 Catalan projects (4 as a PI). He has also co-leaded 5 international technology transfer contracts with the Templeton World Charity Foundation and Huawei. He has published 85 papers in journals indexed in the JCR (58 in the first quartile), including one paper in Science. He has also contributed to 80 conferences. He has authored 12 book chapters and 3 books. His publications have received 7,178 citations (h-index=47, March 2023). He has received 3 research awards in international events and 6 best paper awards. He ranks among the world’s top 2% most cited researchers (2022 Stanford University’s ranking).

Research interests

My research focuses on the study of knowledge and data semantics under an Artificial Intelligence perspective. I work on the development of computational and machine learning methods to understand, manage and transform textual data in analytical algorithms. By means of these methods it is possible to automatize data analyses on (big) textual data and to improve the accuracy of such analyses.

In the last years, I have worked on the application of these semantic methods to the protection of sensitive data, specifically, to anonymize textual data in privacy-challenging scenarios such as document declassification, social media publication or statistical data releases. My contributions resulted in algorithms that preserve the privacy of the subjects while ensuring that the anonymized data are still useful for research. This makes the data protection required by legal frameworks compatible with data analyses that employ personal data.


Semantics, Data Analysis, Machine learning, Data privacy

ICREA Memoir 2023