ERC FUNDED PROJECTS

"A conventional assumption in dynamic models is that agents form their expectations in a very sophisticated manner. In particular, that they have Rational Expectations (RE). We develop some tools to relax this assumption while retaining fully optimal behaviour by agents. We study implications for asset pricing and macro policy. We assume that agents have a consistent set of beliefs that is close, but not equal, to RE. Agents are ""Internally Rational"", that is, they behave rationally given their system of beliefs. Thus, it is conceptually a small deviation from RE. It provides microfoundations for models of adaptive learning, since the learning algorithm is determined by agents’ optimal behaviour. In previous work we have shown that this framework can match stock price and housing price fluctuations, and that policy implications are quite different. In this project we intend to: i) develop further the foundations of internally rational (IR) learning, ii) apply this to explain observed asset price price behavior, such as stock prices, bond prices, inflation, commodity derivatives, and exchange rates, iii) extend the IR framework to the case when agents entertain various models, iv) optimal policy under IR learning and under private information when some hidden shocks are not revealed ex-post. Along the way we will address policy issues such as: effects of creating derivative markets, sovereign spread as a signal of sovereign default risk, tests of fiscal sustainability, fiscal policy when agents learn, monetary policy (more specifically, QE measures and interest rate policy), and the role of credibility in macro policy."

1 970 260 €

Start date: 2013-06-01, End date: 2018-08-31

The objective of this project is to overcome current limitations for antibody production that are inherent to the extant immune system of vertebrates. This will be done by creating an all-in-one artificial/synthetic counterpart based exclusively on prokaryotic parts, devices and modules. To this end, ARISYS will exploit design concepts, construction hierarchies and standardization notions that stem from contemporary Synthetic Biology for the assembly and validation of (what we believe is) the most complex artificial biological system ventured thus far. This all-bacterial immune-like system will not only simplify and make affordable the manipulations necessary for antibody generation, but will also permit the application of such binders by themselves or displayed on bacterial cells to biotechnological challenges well beyond therapeutic and health-related uses. The work plan involves the assembly and validation of autonomous functional modules for [i] displaying antibody/affibody (AB) scaffolds attached to the surface of bacterial cells, [ii] conditional diversification of target-binding sequences of the ABs, [iii] contact-dependent activation of gene expression, [iv] reversible bi-stable switches, and [v] clonal selection and amplification of improved binders. These modules composed of stand-alone parts and bearing well defined input/output functions, will be assembled in the genomic chassis of streamlined Escherichia coli and Pseudomonas putida strains. The resulting molecular network will make the ABs expressed and displayed on the cell surface to proceed spontaneously (or at the user's decision) through subsequent cycles of affinity and specificity maturation towards antigens or other targets presented to the bacterial population. In this way, a single, easy-to-handle (albeit heavily engineered) strain will govern all operations that are typically scattered in a multitude of separate methods and apparatuses for AB production.

2 422 271 €

Start date: 2013-05-01, End date: 2019-04-30

Learning to read is probably one of the most exciting discoveries in our life. Using a longitudinal approach, the research proposed examines how the human brain responds to two major challenges: (a) the instantiation a complex cognitive function for which there is no genetic blueprint (learning to read in a first language, L1), and (b) the accommodation to new statistical regularities when learning to read in a second language (L2). The aim of the present research project is to identify the neural substrates of the reading process and its constituent cognitive components, with specific attention to individual differences and reading disabilities; as well as to investigate the relationship between specific cognitive functions and the changes in neural activity that take place in the course of learning to read in L1 and in L2. The project will employ a longitudinal design. We will recruit children before they learn to read in L1 and in L2 and track reading development with both cognitive and neuroimaging measures over 24 months. The findings from this project will provide a deeper understanding of (a) how general neurocognitive factors and language specific factors underlie individual differences – and reading disabilities– in reading acquisition in L1 and in L2; (b) how the neuro-cognitive circuitry changes and brain mechanisms synchronize while instantiating reading in L1 and in L2; (c) what the limitations and the extent of brain plasticity are in young readers. An interdisciplinary and multi-methodological approach is one of the keys to success of the present project, along with strong theory-driven investigation. By combining both we will generate breakthroughs to advance our understanding of how literacy in L1 and in L2 is acquired and mastered. The research proposed will also lay the foundations for more applied investigations of best practice in teaching reading in first and subsequent languages, and devising intervention methods for reading disabilities.

2 487 000 €

Start date: 2012-05-01, End date: 2017-04-30

"The proposed research project seeks to further our understanding on two important questions for the design of monetary policy: (a) What are the effects of monetary policy interventions on asset price bubbles? (b) How should monetary policy be conducted in the presence of asset price bubbles? The first part of the project will focus on the development of a theoretical framework that can be used to analyze rigorously the implications of alternative monetary policy rules in the presence of asset price bubbles, and to characterize the optimal monetary policy. In particular, I plan to use such a framework to assess the merits of a “leaning against the wind” strategy, which calls for a systematic rise in interest rates in response to the development of a bubble. The second part of the project will seek to produce evidence, both empirical and experimental, regarding the effects of monetary policy on asset price bubbles. The empirical evidence will seek to identify and estimate the sign and response of asset price bubbles to interest rate changes, exploiting the potential differences in the joint behavior of interest rates and asset prices during “bubbly” episodes, in comparison to “normal” times. In addition, I plan to conduct some lab experiments in order to shed some light on the link between monetary policy and bubbles. Participants will trade two assets, a one-period riskless asset and a long-lived stock, in an environment consistent with the existence of asset price bubbles in equilibrium. Monetary policy interventions will take the form of changes in the short-term interest rate, engineered by the experimenter. The experiments will allow us to evaluate some of the predictions of the theoretical models regarding the impact of monetary policy on the dynamics of bubbles, as well as the effectiveness of “leaning against the wind” policies."

799 200 €

Start date: 2014-01-01, End date: 2017-12-31

"Understanding the nature of consciousness is one of the grand outstanding scientific challenges and two of its features stand out: consciousness is defined as the construction of one coherent scene but this scene is experienced with a delay relative to the action of the agent and not necessarily the cause of actions and thoughts. Did evolution render solutions to the challenge of survival that includes epiphenomenal processes? The Conscious Distributed Adaptive Control (CDAC) project aims at resolving this paradox by using a multi-disciplinary approach to show the functional role of consciousness in adaptive behaviour, to identify its underlying neuronal principles and to construct a neuromorphic robot based real-time conscious architecture. CDAC proposes that the shift from surviving in a physical world to one that is dominated by intentional agents requires radically different control architectures combining parallel and distributed control loops to assure real-time operation together with a second level of control that assures coherence through sequential coherent representation of self and the task domain, i.e. consciousness. This conscious scene is driving dedicated credit assignment and planning beyond the immediately given information. CDAC advances a comprehensive framework progressing beyond the state of the art and will be realized using system level models of a conscious architecture, detailed computational studies of its underlying neuronal substrate focusing, empirical validation with a humanoid robot and stroke patients and the advancement of beyond state of the art tools appropriate to the complexity of its objectives. The CDAC project directly addresses one of the main outstanding questions in science: the function and genesis of consciousness and will advance our understanding of mind and brain, provide radically new neurorehabilitation technologies and contribute to realizing a new generation of robots with advanced social competence."

2 469 268 €

Start date: 2014-02-01, End date: 2019-01-31

Given a quantum system, how can one ensure that it (i) is entangled? (ii) random? (iii) secure? (iv) performs a computation correctly? The concept of quantum certification embraces all these questions and CERQUTE’s main goal is to provide the tools to achieve such certification. The need of a new paradigm for quantum certification has emerged as a consequence of the impressive advances on the control of quantum systems. On the one hand, complex many-body quantum systems are prepared in many labs worldwide. On the other hand, quantum information technologies are making the transition to real applications. Quantum certification is a highly transversal concept that covers a broad range of scenarios –from many-body systems to protocols employing few devices– and questions –from theoretical results and experimental demonstrations to commercial products–. CERQUTE is organized along three research lines that reflect this broadness and inter-disciplinary character: (A) many-body quantum systems: the objective is to provide the tools to identify quantum properties of many-body quantum systems; (B) quantum networks: the objective is to characterize networks in the quantum regime; (C) quantum cryptographic protocols: the objective is to construct cryptography protocols offering certified security. Crucial to achieve these objectives is the development of radically new methods to deal with quantum systems in an efficient way. Expected outcomes are: (i) new methods to detect quantum phenomena in the many-body regime, (ii) new protocols to benchmark quantum simulators and annealers, (iii) first methods to characterize quantum causality, (iv) new protocols exploiting simple network geometries (v) experimentally-friendly cryptographic protocols offering certified security. CERQUTE goes at the heart of the fundamental question of what distinguishes quantum from classical physics and will provide the concepts and protocols for the certification of quantum phenomena and technologies.

1 735 044 €

Start date: 2020-01-01, End date: 2024-12-31

There is a fast-growing interest in extending the capabilities of computing systems to perform human-like tasks in an intelligent way. These technologies are usually referred to as cognitive computing. We envision a next revolution in computing in the forthcoming years that will be driven by deploying many “intelligent” devices around us in all kind of environments (work, entertainment, transportation, health care, etc.) backed up by “intelligent” servers in the cloud. These cognitive computing systems will provide new user experiences by delivering new services or improving the operational efficiency of existing ones, and altogether will enrich our lives and our economy. A key characteristic of cognitive computing systems will be their capability to process in real time large amounts of data coming from audio and vision devices, and other type of sensors. This will demand a very high computing power but at the same time an extremely low energy consumption. This very challenging energy-efficiency requirement is a sine qua non to success not only for mobile and wearable systems, where power dissipation and cost budgets are very low, but also for large data centers where energy consumption is a main component of the total cost of ownership. Current processor architectures (including general-purpose cores and GPUs) are not a good fit for this type of systems since they keep the same basic organization as early computers, which were mainly optimized for “number crunching”. CoCoUnit will take a disruptive direction by investigating unconventional architectures that can offer orders of magnitude better efficiency in terms of performance per energy and cost for cognitive computing tasks. The ultimate goal of this project is to devise a novel processing unit that will be integrated with the existing units of a processor (general-purpose cores and GPUs) and altogether will be able to deliver cognitive computing user experiences with extremely high energy-efficiency.

2 498 661 €

Start date: 2019-09-01, End date: 2025-02-28

Current IT research does not respond to the world's multi-cultural reality. It could be argued that we are imposing the paradigms of our market-driven western culture also on IT and that current IT research results will only facilitate the access of a small part of the world’s information to a small part of the world's population. Most IT research is being carried out with a western centred approach and as a result, our data models, cognition models, user models, interaction models, ontologies, … are all culturally biased. This fact is quite evident in music information research, since, despite the world's richness in musical cultures, most of the research is centred on CDs and metadata of our western commercial music. CompMusic wants to break this huge research bias. By approaching musical information modelling from a multicultural perspective it aims at advancing our state of the art while facilitating the discovery and reuse of the music produced outside the western commercial context. But the development of computational models to address the world’s music information richness cannot be done from the West looking out; we have to involve researchers and musical experts immersed in the different cultures. Their contribution is fundamental to develop the appropriate multicultural musicological and cognitive frameworks from which we should then carry our research on finding appropriate musical features, ontologies, data representations, user interfaces and user centred approaches. CompMusic will investigate some of the most consolidated non-western classical music traditions, Indian (hindustani, carnatic), Turkish-Arab (ottoman, andalusian), and Chinese (han), developing the needed computational models to bring their music into the current globalized information framework. Using these music cultures as case studies, cultures that are alive and have a strong influence in current society, we can develop rich information models that can take advantage of the existing information coming from musicological and cultural studies, from mature performance practice traditions and from active social contexts. With this approach we aim at challenging the current western centred information paradigms, advance our IT research, and contribute to our rich multicultural society.

2 443 200 €

Start date: 2011-07-01, End date: 2017-06-30

This project aims at making a breakthrough contribution in the broad area of Control of Partial Differential Equations (PDE) and their numerical approximation methods by addressing key unsolved issues appearing systematically in real-life applications. To this end, we pursue three objectives: 1) to contribute with new key theoretical methods and results, 2) to develop the corresponding numerical tools, and 3) to build up new computational software, the DYCON-COMP computational platform, thereby bridging the gap to applications. The field of PDEs, together with numerical approximation and simulation methods and control theory, have evolved significantly in the last decades in a cross-fertilization process, to address the challenging demands of industrial and cross-disciplinary applications such as, for instance, the management of natural resources, meteorology, aeronautics, oil industry, biomedicine, human and animal collective behaviour, etc. Despite these efforts, some of the key issues still remain unsolved, either because of a lack of analytical understanding, of the absence of efficient numerical solvers, or of a combination of both. This project identifies and focuses on six key topics that play a central role in most of the processes arising in applications, but which are still poorly understood: control of parameter dependent problems; long time horizon control; control under constraints; inverse design of time-irreversible models; memory models and hybrid PDE/ODE models, and finite versus infinite-dimensional dynamical systems. These topics cannot be handled by superposing the state of the art in the various disciplines, due to the unexpected interactive phenomena that may emerge, for instance, in the fine numerical approximation of control problems. The coordinated and focused effort that we aim at developing is timely and much needed in order to solve these issues and bridge the gap from modelling to control, computer simulations and applications.

2 065 125 €

Start date: 2016-10-01, End date: 2022-09-30