Els ICREA

Els professors d'investigació ICREA formen una comunitat dinàmica de científics i investigadors de totes les àrees del coneixement, que contribueixen al progrés de la humanitat amb els seus estudis, interpretacions i preguntes. Entreu i descobriu-ne els increïbles descobriments i troballes:

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    Ruth de Diego-Balaguer
    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
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    Gianni De Fabritiis
    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
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    Coen de Graaf
    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
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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
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    Susana de la Luna
    de la Luna Gargantilla, Susana
    Research Professor at
    Centre de Regulació Genòmica (CRG)
    Life & Medical Sciences
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    Research interests

    Protein kinases are central to all cellular processes in eukaryotes, and often linked to disease when they are altered. My group works on a family of protein kinases known as DYRK (dual-specificity tyrosine-regulated kinases), whose members -DYRK1A, DYRK1B, DYRK2, DYRK3, DYRK4- participate in the regulation of processes critical for cell viability and homeostasis. In general, alterations in DYRKs (expression or mutation) are linked to different cancer types. In addition, mutations in several DYRK genes are associated to developmental disorders, as in the case of the DYRK1A haploinsufficiency syndrome or the DYRK1B-associated metabolic syndrome. My group aims to dissect how DYRK activities are linked to human pathology. We are particularly interested on the DYRK-associated activities that impact on the regulation of expression programs either directly on chromatin or indirectly through modulation of signaling pathways.

    Key words

    cell signaling, protein kinases, transcriptional regulation, DYRK kinases, rare disease

    ORCID

    : orcid.org/0000-0001-7765-916X

    RESEARCHER ID

    : E-9553-2015
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    Hugues de Riedmatten
    de Riedmatten, Hugues
    Research Professor at
    Institut de Ciències Fotòniques (ICFO)
    Engineering Sciences
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    Research interests

    Hugues de Riedmatten leads the Quantum Photonics group at ICFO. His research interests are in quantum information science (QIS) and quantum optics. QIS is a research field that aims at controlling quantum coherence in light and matter in order to enable new information processing capabilities impossible with classical resources. He is interested in the quantum control of light matter interaction between single photons and atomic ensembles implemented with rare-earth doped solids and cold atomic gases. Other research lines include quantum non-linear optics with Rydberg atoms, and the detection and manipulation of single ions in the solid-state. The goal is to develop the quantum technology to implement quantum information networks and quantum repeaters. A more fundamental goal is to enable the observation of fascinating quantum effects, such as entanglement, with distant material systems and to explore the limits of quantum coherence in complex material systems.

    Key words

    Quantum Information, Quantum optics, Quantum memory, Entanglement