Back Four innovative projects led by researchers linked to UPF obtain grants from the BBVA Foundation
Four innovative projects led by researchers linked to UPF obtain grants from the BBVA Foundation
They are José García Montalvo and Gábor Lugosi (Department of Economics and Business), Alberto Carrio (Department of Law), and Mar Albà Soler (Hospital del Mar Medical Research Institute Foundation, IMIM). Their research will focus, respectively, on the housing market prices in Catalonia, new models to extract information from data analysis, artificial intelligence in the world of sport, and the improvement of mathematical models to increase the effectiveness of immunotherapy.
Four researchers linked to Pompeu Fabra University have obtained grants under the 2021 announcement of Grants for Scientific Research Projects of the BBVA Foundation, whose aim is to give support to innovative knowledge and scientific research and their outreach to society.
Of the 620 applications submitted in the five areas that make up the call (Mathematics, Climate Change and Ecology, Biomedicine, Social Sciences and Philosophy), 35 projects have been selected (twelve of which will be carried out in Catalonia), which means direct support to a total of 204 researchers.
José García Montalvo and Gábor Lugosi (Department of Economics and Business) have been chosen in the areas of Social Sciences and Mathematics, respectively; Alberto Carrio (Department of Law) will carry out a project within the area of Philosophy, and Mar Albà (Hospital del Mar Medical Research Institute, IMIM, a centre with participation by UPF), is one of those chosen in the Biomedicine category.
The grants, which the BBVA Foundation has awarded since 2014, are each endowed with 30,000 euros in the area of Philosophy (16 projects supported in total), 50,000 in the Social Sciences (5 projects), 125,000 euros in the Environment (4 projects) and 150,000 in the areas of Mathematics (4 projects) and Biomedicine (4 projects), in addition to 2 projects with aid of 100,000 euros to develop new epidemiological models of SARS-CoV-2.
Effects of second-generation price controls on the rental market: the case of Catalonia (PLACAT)
José García Montalvo, a full professor of Applied Economics at the Department of Economics and Business and coordinator of the Applied Macroeconomics and Quantitative Methods Research Group, is the main researcher of this project, which proposes using microdata to analyse the effect of the limitations to the growth of rental prices in Catalonia. This database, composed of anonymized microdata from more than half a million households, will allow making substantial contributions to the literature on the effect of second-generation price caps.
The project proposes using micro data to analyse the effect of the limitations to the growth of rental prices in Catalonia
To regulate the housing market, in September 2020 Catalonia introduced price control policies, although the Spanish Constitutional Court has just annulled them, deeming them contrary to the Spanish magna carta. This situation allows the possibility of studying the effects that the introduction of the control measure had on the market and its prices, as well as the consequences that the withdrawal of these limitations is already having. “Some of the aspects on which the project will provide information will be the evolution of prices, the average returns on operations, what percentage of dwellings have been expelled from the rental market, and the extent to which sanctions for non-compliance have been effective”, José García Montalvo states.
New models to extract relevant information from data analysis
There is currently a demand for approaches based on mathematical principles to extract useful and relevant information from data for a better theoretical understanding of existing models. Gábor Lugosi, an ICREA research professor with the Department of Economics and Business at UPF and coordinator of the Statistics and Operational Research Research Group, will lead a project that will develop new models that support non-uniform data regarding deep learning and integrate external information to be able to draw more solid conclusions around these data.
“Perhaps the most important theoretical challenge in machine learning is to understand the almost miraculous performance of deep learning algorithms"
This approach is important, since deep learning has currently achieved major breakthroughs in data analysis, obtaining unprecedented predictive capacity in contexts that other mathematical tools cannot encompass. Nevertheless, standard statistical theory is not able to explain the great power of deep learning, which is known to work, but why it works is not. “Perhaps the most important theoretical challenge in machine learning is to understand the almost miraculous performance of deep learning algorithms”, Gábor Lugosi reflects.
Detecting and solving problems arising from the use of artificial intelligence in the world of sport
The use of artificial intelligence in sport has provided several tools, ranging from systems to help refereeing to injury prevention. However, its use raises conflicts of a diverse nature. The project to be carried out by Alberto Carrio, a professor of Philosophy of Law at the UPF Department of Law and member of the UPF Sports_Lab Study Centre, aims to analyse the various ethical issues raised by applications of AI in sport and propose certain regulatory measures needed to address them.
“The aim of the project is to design an ethical framework, for both preventive and consultative purposes, that facilitates the safe and appropriate use of AI in sport”
The basic assumptions on which the analysis will be carried out are sport ethics and the principles of good governance, as reflected in the Fundamental Principles of the Olympic Charter, the Code of Ethics and the Universal Basic Principles of Good Governance. “The aim of the project is to design an ethical framework, for both preventive and consultative purposes, that facilitates the safe and appropriate use of AI in sport”, Alberto Carrio assures.
Mathematical models to improve the effectiveness of immunotherapy for bladder cancer
Immunotherapy is a series of treatments aimed at improving the immune system’s ability to fight cancer, and is one of today’s great hopes against this disease. It is already being applied successfully in certain neoplasms, but for unknown reasons, it is not effective in all patients. Mar Albà, an ICREA research professor at the Hospital del Mar Medical Research Institute (IMIM), where she is co-director of the Research Programme in Biomedical Informatics (GRIB), is the principal investigator of a project that will develop computational models with which, through genomic-type markers, it can be better understood what determines that some patients respond to therapy and others do not.
“With the help of a multidisciplinary team, we wish to develop new computational methods in which different markers are integrated, including the load of mutations, but also the number of transcripts that are specific to each tumour”
“With the help of a multidisciplinary team, we wish to develop new computational methods in which different markers are integrated, including the load of mutations, but also the number of transcripts that are specific to each tumour”, Mar Albà explains. To this end, the project will use DNA and RNA sequencing data collected from hundreds of patients with advanced bladder cancer, one of the most frequent and malignant in developed countries, and with few treatment options in metastasis.