The projects of the researchers Miguel Valencia Ustárroz, from Tecnun-Escuela de Ingeniería, and Francisco Planes Pedreño, from Tecnun-Escuela de Ingeniería. Cima; and Francisco Planes Pedreño, Full Professor of Tecnun-School of Engineering, have been recognized in the first edition of the awards of the high school of Science of the data and Artificial Intelligence of the University of Navarra (DATAI). These projects highlight the application of the science of data in an interdisciplinary way in the research and treatment of neurological diseases or cancer therapies.

The submission of the awards was attended by the director of DATAI University of Navarra, Jesús López Fidalgo; the Vice President of Office of Academic Affairs, Secundino Fernández; and the director of the Artificial Intelligence and the Future of Management Initiative of IESE Business School, Sampsa Samila.

The goal of the awards, addressed to all DATAI researchers, is to recognize especially relevant scientific contributions in the field of science of data and artificial intelligence. The awards value originality, innovation and contribution with the double goal to encourage research work as well as its projection to society. Each award is endowed with 3,000 euros for the development of the research.

Jesús López Fidalgo valued the quality and the multidisciplinarity of the recognized projects and thanked the partnership of BBVA and the Government of Navarra with DATAI. "It is estimated that by 2030, Artificial Intelligence will significantly influence more than 8.5 billion people, across all sectors on an unprecedented scale. According to a study published in the journal Nature, AI could help achieve 79% of the development Sustainable Goals. From this follows the opportunity to connect the research groups working on this topic and leverage different competencies in development and AI," he said. 

The project of Miguel Valencia, researcher of Cima, belonging to area "Health Analytics" of DATAI, uses different methodologies in order to record, analyze and model brain activity in physiological conditions and under the effect of neurological diseases. result of the partnership between life science researchers, clinicians and scientists from data, proposes a flow from work to train artificial intelligence tools that can automatically detect abnormal events in brain activity recorded via EEG. "The work flow is easily adaptable to multiple real-world scenarios and was designed with an interactive and user-friendly approach that makes it manageable for clinical and experimental researchers without programming skills. However, it is designed so that data scientists can optimize it for more specific scenarios, improving the transfer of knowledge between different disciplines," he explains.

On the other hand, the research presented by Francis Planes is framed in the field of computational biology and cancer therapies. In the context of precision oncology, they have developed different algorithms to classify patients, identify new therapeutic targets and predict the result of cancer therapies. "One of the great challenges of artificial intelligence is to build robust algorithms that are able to learn from data and not memorize them. For this, the selection of the most relevant variables of the problem is a crucial step, especially in the biomedical field where we have information from a limited issue of patients, but thousands of measurable variables. In this contribution, we have developed a new method of variable selection that improves the existing ones in the literature. We have applied it to cancer therapy response prediction models, but it can be applied more globally to other problems".

In the lecture that he gave during the event, Sampsa Samila, addressed the artificial intelligence models and their economic impact. He first referred to those that emerged for images up to the current ChatGPT. Samila explained how these models work, which have generated enthusiasm but, at the same time, concern about their potential impact; and the commercial and personal implications they entail. 

Transversal, interdisciplinary and service vocation

The high school of Science of the data and AI (DATAI) was created in December 2019 with a transversal, interdisciplinary and service vocation. Currently, more than 80 researchers from different Schools and centers of the University of Navarra, and external companies such as BBVA integrate the staff of the center. In the last three years, research projects have been developed in different fields. 

DATAI has worked with companies, including BBVA, Gamesa, AIN, INFOPERMIT or Human AI; and institutions such as the Ministry of Science and the Departments of the Government of Navarra for Universities, Industry, Economics and Justice and Immigration. More than 300 people have been trained in science from data through the Master's Degree in Big Data Science and the courses given from the high school. In addition, 70 BBVA employees have received the scientist certification from data and 10 are developing their industrial doctoral thesis at framework of high school.