Los ICREA

Los catedráticos de investigación de ICREA forman una comunidad dinámica de científicos e investigadores de todas las áreas del conocimiento, que contribuyen al progreso de la humanidad con sus estudios, interpretaciones y cuestionamientos. Entre y descubra sus increíbles descubrimientos y hallazgos:

Courbin, Frédéric

Universitat de Barcelona (UB)

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Courbin, Frédéric
Research Professor at
Universitat de Barcelona (UB)
Experimental Sciences & Mathematics
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Research interests

My research is in observational cosmology and in gravitational lensing in all regimes: strong, weak, micro and milli. I contributed to develop the field of time delay cosmography with strongly lensed quasars, to measure the Hubble constant and address the so-called Hubble tension between early and late Universe measurements. I was granted and ERC Advanced Grant in 2018, COSMICLENS, specifically on time delay cosmography.

I'm also a builder member of the ESA-NASA Euclid mission, in which I've been involved from the very beginning. In Euclid, I'm the current lead of the strong lensing science working group. I'm active in the Rubin-LSST time domain survey and is part of the Spanish-led ESA-ARRAKIHS mission to study the nature of Dark Matter with ultra-deep observations of local galaxies.

A significant part of my research is also in pure signal processing, and in particular image deconvolution and morpho-spectral decomposition with sparse regularization and machine learning techniques.

Key words
Gravitational lensing (strong and micro), time delays, image processing, observational cosmology

ORCID
: 0000-0003-0758-6510
Daura Ribera, Xavier

Universitat Autònoma de Barcelona (UAB)

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Daura Ribera, Xavier
Research Professor at
Universitat Autònoma de Barcelona (UAB)
Life & Medical Sciences
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Research interests

The main objective of our research group is the development of new strategies to combat infections by multidrug-resistant (MDR) bacteria, in particular of the Gram-negative (GN) group. The increasing emergence and spread of MDR pathogens constitutes at present one of the major threats to public health. The shortage of effective antimicrobials for the treatment of MDR GN infections is particularly critical as cases of pan-resistance are not uncommon. The discovery of new drug targets and modes of action (MoA), less prone to the development of resistance, has therefore become a pressing need. In parallel, the development of effective vaccines may offer a solution for high-risk population groups. Our team combines a range of computational and experimental techniques for the identification of antimicrobial-target candidates with new MoA and vaccine candidates eliciting prescribed resposes. Much of this work is done in collaboration with the group of Bacterial Molecular Genetics of IBB.

Key words
multidrug resistance, synthetic vaccinology, antimicrobials, bioinformatics, biomolecular modelling, biomolecular simulation

ORCID
: 0000-0001-9235-6730

RESEARCHER ID
: C-9275-2009
de Diego Balaguer, Ruth

Universitat de Barcelona (UB)

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de Diego Balaguer, Ruth
Research Professor at
Universitat de Barcelona (UB)
Social & Behavioural Sciences
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Research interests

My research combines information from brain-damaged patients, developmental populations and brain-imaging in healthy individuals to understand whether words and rules of language require different neural and cognitive mechanisms to be acquired since the earliest stages of contact with a new language. I am particularly interested in i) the role of the attentional systems in the acquisition of different aspects of language; ii) the role of the striatum as a brain structure that could make the interface between language and other cognitive functions necessary in the learning process; and iii) how is the acquired information consolidated and modified when we learn new additional information.

Key words
Language acquisition, rule learning, striatum

ORCID
: orcid.org/0000-0002-2357-5195

RESEARCHER ID
: V-2131-2017
De Fabritiis, Gianni

Universitat Pompeu Fabra (UPF)

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De Fabritiis, Gianni
Research Professor at
Universitat Pompeu Fabra (UPF)
Experimental Sciences & Mathematics
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Research interests

The group's research interests are rooted in the applications of computation to science, where we regard intelligence as a form of computation itself.

1) Molecular simulation and machine learning. We use computation such as physics-based simulations and modern machine learning to provide novel, innovative methodological approaches in biomedicine.

2) Computational intelligence. We investigate machine learning methods that would bring machine intelligence closer to human-level intelligence. We train intelligence agents using reinforcement learning in virtual environments, we built scalable software for reinforcement learning and low-sample learning.

Key words
Computer simulations, Machine learning, Machine intelligence
de Graaf, Coen

Universitat Rovira i Virgili (URV)

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de Graaf, Coen
Research Professor at
Universitat Rovira i Virgili (URV)
Experimental Sciences & Mathematics
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Research interests

Electron transfer between molecules plays a fundamental role in the conversion of sunlight to useful forms of energy. This can take place by the generation of electricity in photovoltaic cells or indirectly by making possible catalytic reactions. Electron transfer processes can be studied in great detail through computational schemes and this has undoubtably helped to make capturing sunlight more profitable. In our group we are developing new computational schemes based on non-orthogonal configuration interaction to explore alternatives to the existing theoretical methods. The complementary information generated through this new approach can provide us very interesting information about the singlet fission process in which incoming sunlight produces (theoretically) twice as much electricity as in standard solar cells based on silicon. We also apply the non-orthogonal computational schemes to other areas such as molecular magnetism and core-level spectroscopy.

Key words
Theoretical Chemistry; Transition metal compounds; Light induced magnetism

ORCID
: http://orcid.org/0000-0001-8114-6658

RESEARCHER ID
: A-5677-2008
de la Cruz Montserrat, Francisco Javier

Vall d'Hebron Institut de Recerca (VHIR)

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de la Cruz Montserrat, Francisco Javier
Research Professor at
Vall d'Hebron Institut de Recerca (VHIR)
Life & Medical Sciences
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Research interests

Our main research aims at understanding the molecular basis of hereditary disease, integrating two complementary aspects: the molecular impact of causative variants and how genetic background regulates the propagation of this impact. At a technical level, to reach our objective, we integrate the results of the most advanced genomic experiments (single-cell, Hi-C, etc.) using state-of-the-art machine learning tools. To enhance the biomedical reach of our research, we work in collaboration with clinical groups from different hospitals. As a result of these efforts, we have recently made significant advances in understanding the functional effect of BRCA1/2 protein variants underlying hereditary breast and ovarian cancers. Finally, mention that we are also devoting an important part of our efforts to the fundamental study of epigenetic processes, to reach a full picture of which phenomena contribute to the generation of phenotype and, more precisely, of clinical phenotype.

Key words
Computational Biology, In silico tools, Machine Learning, Artificial Intelligence, Protein Mutations, Molecular Diagnostics, Bioinformatics, Epigenetics, Systems Biology

ORCID
: 0000-0002-9738-8472