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:

Marcet Torrens, Albert

Centre de Recerca en Economia Internacional (CREI)

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Marcet Torrens, Albert
Research Professor at
Centre de Recerca en Economia Internacional (CREI)
Social & Behavioural Sciences
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Research interests

RECURSIVE CONTRACTS many models in social sci. involve dynamic optimization with forward-looking constraints (, e.g., policy analysis or contracts). These are not amenable to a standard Bellman equation treatment. We propose a new way of formulating recursively these dynamic optimization problems. Our approach has a very wide range of applications. ASSET PRICES AND LEARNING Asset prices show huge fluctuations over time that are hard to reconcile with actual fundamentals. We study agents that behave rationally and have an empirically plausible model of asset prices to explain asset behavior. DEBT MANAGEMENT recent debt crisis highlight the importance of bond portfolios issued by governments (debt management). We analyze the optimal combination of bond maturities that should be issued over the business cycle. FISCAL POLICY: this is a main them in macroeconomics, we use the above tools to study fiscal pollicy, speciallly with heterogeneous agents.

Key words
Macroeconomics, Time Series, Models of Learning, Fiscal policy, financial economics
Markovsky, Ivan

Centre Internacional de Mètodes Numèrics a Enginyeria (CIMNE)

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Markovsky, Ivan
Research Professor at
Centre Internacional de Mètodes Numèrics a Enginyeria (CIMNE)
Engineering Sciences
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Research interests

The objective of my research is unsupervised data-driven analysis and design of dynamical systems. The classical paradigm splits the problem into model identification and model-based design. In general, there is no separation principle for modeling and design, so that the two-stage approach may be suboptimal. I am investigating an alternative direct data-driven paradigm that combines modeling and design into one joint problem. In 2010, I proposed a solution approach for data-driven design based on structured low-rank approximation (ERC starting grant). More recently, I investigated convex relaxation, subspace, and regularization methods. Current topics of interest are data-driven methods for nonlinear, time-varying, and distributed systems. Besides data-driven design, I am interested in methods for teaching and learning that are effective in training critical thinking and creativity. I am an advocate of the open peer review as an alternative to the traditional closed review system.

Key words
system identification, data-driven modeling, low-rank approximation

ORCID
: 0000-0001-9976-9685

RESEARCHER ID
: HIK-0832-2022
Marquès Bonet, Tomàs

Universitat Pompeu Fabra (UPF)

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Marquès Bonet, Tomàs
Research Professor at
Universitat Pompeu Fabra (UPF)
Life & Medical Sciences
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Research interests

What makes us human? This is a fundamental question in many disciplines. Our team analyzes a wide range of genome variants to determine processes, variants and molecular features that are intrinsic to our species. To do so, we study full genome, epigenomes and transcriptomic sequences of humans and great apes for a better understanding of human specific features.

Key words
Genomics, copy number variation, primates, evolution, structural variation

ORCID
: orcid.org/0000-0002-5597-3075
Marques Silva, Joao P

Universitat de Lleida (UdL)

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Marques Silva, Joao P
Research Professor at
Universitat de Lleida (UdL)
Engineering Sciences
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Research interests

My main field of research is Artificial Intelligence (AI). At present, my research focuses on applying methods of formal logic and automated reasoning in computing explanations of complex machine learning (ML) models, i.e. the well-known problem of eXplainable AI (XAI). One key aspect of my work on XAI is the rigor of computed explanations. Over the last few years, my work on XAI revealed key connections between rigorous explanations with several other fields of computer science, including formal logic, automated reasoning, optimization, and game theory, among others. In addition to my work on logic-based XAI, I maintain research interests in developing automated reasoners for solving computationally hard problems, including decision, optimization and function problems.

Key words
Explainable AI; Constraint Programming; Boolean Satisfiability; Formal Methods

ORCID
: 0000-0002-6632-3086

RESEARCHER ID
: C-9162-2009
Martí, Genoveva

Universitat de Barcelona (UB)

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Martí, Genoveva
Research Professor at
Universitat de Barcelona (UB)
Humanities
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Research interests

My research focuses on the exploration of reference, the relation between words and pieces of the world that makes it possible to talk about things. Traditionally, reference has been conceived as mediated by our cognitive perspective on things. On this view, which objects we talk about is determined by the concepts we associate with the expressions we use. Against this view I defend an approach to semantics according to which reference is not determined just by our mental states nor by the concepts we entertain; it rather depends on causal and social factors that are external to our mind. My research topics are connected to research areas in Linguistics and Psychology. I also have worked on the explanation of legal disputes from the point of view of different theories of reference, on the role of the theory of reference in the defense of scientific realism and on the impact of experimental data on semantics. A critical paper on experimental semantics has been recently accepted by dialectica and is available online ( https://doi.org/10.48106/dial.v74.i3.06 )

Key words
Philosophy of Language, Theory of Reference, Modality, Analytic Philosophy

ORCID
: 0000-0003-1269-4655
Martí-Renom, Marc

Centre Nacional d'Anàlisi Genómica (CNAG)

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Martí-Renom, Marc
Research Professor at
Centre Nacional d'Anàlisi Genómica (CNAG)
Life & Medical Sciences
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Research interests

How biomolecules fold and function in a three-dimensional space is one of the most challenging questions in biology. For example, we have limited knowledge on how the 2-meter-long DNA molecule folds in the micro-sized nucleus or how RNA, proteins and small chemical compounds fold and interact to perform their most basic functions of the cell. Our research group employ the laws of physics and the rules of evolution to develop and apply experimental and computational methods for predicting the 3D structures of macromolecules and their complexes.

Key words
Genome organization, RNA, structural biology, computational biology

ORCID
: 0000-0002-0151-4279

RESEARCHER ID
: A-1836-2010