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UC3M awarded two Fundación BBVA grants for highly innovative scientific research


Two Universidad Carlos III de Madrid (UC3M) research projects have been chosen by the Fundación BBVA in its call for grants for 25 highly innovative scientific research teams. The projects that will obtain funding were chosen out of a field of 618 applicants.  UC3M is second among Spanish universities in the number of grants obtained in this edition.

Investigación Vanguardia Fundación BBVA

The projects tackle a wide spectrum of topics of social interest in the areas of Biomedicine, Biology and Environmental and Earth Sciences, Economics and the Digital Society, Big Data and Digital Humanities. The teams are characterized by a high level of multidisciplinarity (between 3 and 21 researchers per project) with most of the team leaders being full professors (16) or associate professors (5).

This Fundación BBVA grant program for scientific research teams seeks to boost basic, translational or applied research in areas of pronounced social interest.  The initiative is based on the support of excellence and innovative talent, with the selection process undertaken by committees of experts in each of the fields.   

An algorithm to monitor psychiatric patients

The UC3M projects receiving these grants are within the framework of two areas.  In the area of Big Data, the project led by the Full Professor from the University’s Department of Signal Theory and Communications, Antonio Artés Rodríguez, focuses on the creation of an algorithm that characterizes the behavior of psychiatric patients. For that purpose, data will be collected on a large scale to determine patients’ mental states and as such help patients under psychiatric care more efficiently.  The researchers will gather the data of patients- who previously have given their consent, guaranteeing their privacy- in collaboration with the Hospital Universitario Fundación Jiménez Díaz. This information will be obtained through mobile phones, which monitor patients’ mobility, activity or sleep. Afterwards, through Deep Learning, these disperse and heterogeneous data will be used by the researchers to transform them into interpretable models that can be of help to these patients.  

The impact of this research is that it will enable the patient’s state to be evaluated automatically.  A psychiatrist will be able to determine their behavior beyond the confines of the office, and as such, be aware of how the patient reacts to a treatment or to therapy to know if it is working or if there is some pattern change, and accordingly make an appropriate decision. The methodology in this study is not only applicable to psychiatry, but rather can be extrapolated to any field in which human behavior is relevant, such as finance, medicine in general, security/safety, advertising or marketing.  

Social networks as a source for behavior analysis

The other UC3M research project awarded a grant from BBVA is within the framework of the area of the Economy and the Digital Society.  The team, led by the UC3M Full Professor of Economics, Ignacio Ortuño Ortín, is made up of engineers and economists and uses social networks as a source for research data.  It is based on the idea that the information that users put on their social networks can be used in the same way as it is in surveys, in order to create a large database on preferences and behaviors.  In this way, the team will analyze the (aggregated and anonymous) information that Facebook provides on the preferences of its 2 billion users to draw up maps and measure the cultural distances between different social groups.   

The aim of this analysis is to determine, for example, the degree of integration of immigrants in a certain society (comparing the interests of the immigrants with those of the local inhabitants.) The researchers have gathered a large quantity of information from social networks and have established that is more complete than traditional surveys, according to which they believe that they would be able to develop stability indexes for every country in the world, including those where survey data is usually scarce.