ERC FUNDED PROJECTS

The two biggest challenges in solving practical optimization problems are computational intractability, and the presence of uncertainty: most problems are either NP-hard, or have incomplete input data which makes an exact computation impossible. Recently, there has been a huge progress in our understanding of intractability, based on spectacular algorithmic and lower bound techniques. For several problems, especially those with only local constraints, we can design optimum approximation algorithms that are provably the best possible. However, typical optimization problems usually involve complex global constraints and are much less understood. The situation is even worse for coping with uncertainty. Most of the algorithms are based on ad-hoc techniques and there is no deeper understanding of what makes various problems easy or hard. This proposal describes several new directions, together with concrete intermediate goals, that will break important new ground in the theory of approximation and online algorithms. The particular directions we consider are (i) extend the primal dual method to systematically design online algorithms, (ii) build a structural theory of online problems based on work functions, (iii) develop new tools to use the power of strong convex relaxations and (iv) design new algorithmic approaches based on non-constructive proof techniques. The proposed research is at the cutting edge of algorithm design, and builds upon the recent success of the PI in resolving several longstanding questions in these areas. Any progress is likely to be a significant contribution to theoretical computer science and combinatorial optimization.

1 519 285 €

Start date: 2014-05-01, End date: 2019-04-30

Our field is cryptology. Our overarching objective is to advance significantly the frontiers in design and analysis of high-security cryptography for the future generation. Particularly, we wish to enhance the efficiency, functionality, and, last-but-not-least, fundamental understanding of cryptographic security against very powerful adversaries. Our approach here is to develop completely novel methods by deepening, strengthening and broadening the algebraic foundations of the field. Concretely, our lens builds on the arithmetic codex. This is a general, abstract cryptographic primitive whose basic theory we recently developed and whose asymptotic part, which relies on algebraic geometry, enjoys crucial applications in surprising foundational results on constant communication-rate two-party cryptography. A codex is a linear (error correcting) code that, when endowing its ambient vector space just with coordinate-wise multiplication, can be viewed as simulating, up to some degree, richer arithmetical structures such as finite fields (or products thereof), or generally, finite-dimensional algebras over finite fields. Besides this degree, coordinate-localities for which simulation holds and for which it does not at all are also captured. Our method is based on novel perspectives on codices which significantly widen their scope and strengthen their utility. Particularly, we bring symmetries, computational- and complexity theoretic aspects, and connections with algebraic number theory, -geometry, and -combinatorics into play in novel ways. Our applications range from public-key cryptography to secure multi-party computation. Our proposal is subdivided into 3 interconnected modules: (1) Algebraic- and Number Theoretical Cryptanalysis (2) Construction of Algebraic Crypto Primitives (3) Advanced Theory of Arithmetic Codices

2 447 439 €

Start date: 2017-10-01, End date: 2022-09-30

For over a century it was believed that ammonium could only be oxidized by microbes in the presence of oxygen. The possibility of anaerobic ammonium oxidation (anammox) was considered impossible. However, about 10 years ago the microbes responsible for the anammox reaction were discovered in a wastewater plant. This was followed by the identification of the responsible bacteria. Recently, the widespread environmental occurrence of the anammox bacteria was demonstrated leading to the realization that anammox bacteria may play a major role in biological nitrogen cycling. The anammox bacteria are unique microbes with many unusual properties. These include the biological turn-over of hydrazine, a well known rocket fuel, the biological synthesis of ladderane lipids, and the presence of a prokaryotic organelle in the cytoplasma of anammox bacteria. The aim of this project is to obtain a fundamental understanding of the metabolism and ecological importance of the anammox bacteria. Such understanding contributes directly to our environment and economy because the anammox bacteria form a new opportunity for nitrogen removal from wastewater, cheaper, with lower carbon dioxide emissions than existing technology. Scientifically the results will contribute to the understanding how hydrazine and dinitrogen gas are made by the anammox bacteria. The research will show which gene products are responsible for the anammox reaction, and how their expression is regulated. Furthermore, the experiments proposed will show if the prokaryotic organelle in anammox bacteria is involved in energy generation. Together the environmental and metabolic data will help to understand why anammox bacteria are so successful in the biogeochemical nitrogen cycle and thus shape our planets atmosphere. The different research lines will employ state of the art microbial and molecular methods to unravel the exceptional properties of these highly unusual and important anammox bacteria.

2 500 000 €

Start date: 2009-01-01, End date: 2013-12-31

"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

For a large family of computational problems collectively known as constrained optimization and satisfaction problems (CSPs), four decades of research in algorithms and computational complexity have led to a theory that tries to classify them as algorithmically tractable vs. intractable, i.e. polynomial-time solvable vs. NP-hard. However, there remains an important gap in our knowledge in that many CSPs of interest resist classification by this theory. Some such problems of practical relevance include fundamental partition problems in graph theory, isomorphism problems in combinatorics, and strategy-design problems in mathematical game theory. To tackle this gap in our knowledge, the research of the last decade has been driven either by finding hard instances for algorithms that solve tighter and tighter relaxations of the original problem, or by formulating new hardness-hypotheses that are stronger but admittedly less robust than NP-hardness. The ultimate goal of this project is closing the gap between the partial progress that these approaches represent and the original classification project into tractable vs. intractable problems. Our thesis is that the field has reached a point where, in many cases of interest, the analysis of the current candidate algorithms that appear to solve all instances could suffice to classify the problem one way or the other, without the need for alternative hardness-hypotheses. The novelty in our approach is a program to develop our recent discovery that, in some cases of interest, two methods from different areas match in strength: indistinguishability pebble games from mathematical logic, and hierarchies of convex relaxations from mathematical programming. Thus, we aim at making significant advances in the status of important algorithmic problems by looking for a general theory that unifies and goes beyond the current understanding of its components.

1 725 656 €

Start date: 2015-06-01, End date: 2020-05-31

Natural selection is supposed to keep lethal alleles (dysfunctional or deleted copies of crucial genes) in check. Yet, in a balanced lethal system the frequency of lethal alleles is inflated. Because two forms of a chromosome carry distinct lethal alleles that are reciprocally compensated for by functional genes on the alternate chromosome form, both chromosome forms – and in effect their linked lethal alleles – are required for survival. The inability of natural selection to purge balanced lethal systems appears to defy evolutionary theory. How do balanced lethal systems originate and persist in nature? I suspect the answer to this pressing but neglected research question can be found in the context of supergenes in a balanced polymorphism – a current, hot topic in evolutionary biology. Chromosome rearrangements can lock distinct beneficial sets of alleles (i.e. supergenes) on two chromosome forms by suppressing recombination. Now, balancing selection would favour possession of both supergenes. However, as a consequence of suppressed recombination, unique lethal alleles could become fixed on each supergene, with natural selection powerless to prevent collapse of the arrangement into a balanced lethal system. I aim to explain the evolution of balanced lethal systems in nature. As empirical example I will use chromosome 1 syndrome, a balanced lethal system observed in newts of the genus Triturus. My research team will: Reconstruct the genomic architecture of this balanced lethal system at its point of origin [PI project]; Conduct comparative genomics with related, unaffected species [PhD project]; Determine gene order of the two supergenes involved [Postdoc project I]; and Model the conditions under which this balanced lethal system could theoretically have evolved [Postdoc project II]. Solving the paradox of chromosome 1 syndrome will allow us to understand balanced lethal systems in general and address the challenges they pose to evolutionary theory.

1 499 869 €

Start date: 2019-02-01, End date: 2024-01-31

Increases in nutrient availability and temperature, and changes in precipitation patterns and biodiversity are important components of global environmental change. Thus, it is imperative to understand their impacts on the functioning of natural ecosystems. Substantial research efforts are being currently devoted to predict how biodiversity will respond to global change. However, little is known on the relative importance of biodiversity against other attributes of biotic communities, such as species cover and spatial pattern, as a driver of ecosystem processes. Furthermore, the effects of global change on the relationships between these attributes and ecosystem functioning are virtually unknown. This project aims to evaluate the relationships between community attributes (species richness, composition, evenness, cover, and spatial pattern) and key processes related to ecosystem functioning under different global change scenarios. Its specific objectives are to: i) evaluate the relative importance of community attributes as drivers of ecosystem functioning, ii) assess how multiple global change drivers will affect key ecosystem processes, iii) test whether global change drivers modify observed community attributes-ecosystem functioning relationships, iv) develop models to forecast global change effects on ecosystem functioning, and v) set up protocols for the establishment of mitigation actions based on the results obtained. They will be achieved by integrating experimental and modeling approaches conducted with multiple biotic communities at different spatial scales. Such integrated framework has not been tackled before, and constitutes a ground breaking advance over current research efforts on global change. This proposal will also open the door to new research lines exploring the functional role of community attributes and their importance as modulators of ecosystem responses to global change.

1 463 374 €

Start date: 2010-01-01, End date: 2015-09-30

Our ability to think, to memorize and focus our thoughts depends on acetylcholine signaling in the brain. The loss of cholinergic signalling in for instance Alzheimer’s disease strongly compromises these cognitive abilities. The traditional view on the role of cholinergic input to the neocortex is that slowly changing levels of extracellular acetylcholine (ACh) mediate different arousal states. This view has been challenged by recent studies demonstrating that rapid phasic changes in ACh levels at the scale of seconds are correlated with focus of attention, suggesting that these signals may mediate defined cognitive operations. Despite a wealth of anatomical data on the organization of the cholinergic system, very little understanding exists on its functional organization. How the relatively sparse input of cholinergic transmission in the prefrontal cortex elicits such a profound and specific control over attention is unknown. The main objective of this proposal is to develop a causal understanding of how cellular mechanisms of fast acetylcholine signalling are orchestrated during cognitive behaviour. In a series of studies, I have identified several synaptic and cellular mechanisms by which the cholinergic system can alter neuronal circuitry function, both in cortical and subcortical areas. I have used a combination of behavioral, physiological and genetic methods in which I manipulated cholinergic receptor functionality in prefrontal cortex in a subunit specific manner and found that ACh receptors in the prefrontal cortex control attention performance. Recent advances in optogenetic and electrochemical methods now allow to rapidly manipulate and measure acetylcholine levels in freely moving, behaving animals. Using these techniques, I aim to uncover which cholinergic neurons are involved in fast cholinergic signaling during cognition and uncover the underlying neuronal mechanisms that alter prefrontal cortical network function.

1 499 242 €

Start date: 2011-11-01, End date: 2016-10-31

Many questions in science, policy making and everyday life are of a causal nature: how would changing A influence B? Causal inference, a branch of statistics and machine learning, studies how cause-effect relationships can be discovered from data and how these can be used for making predictions in situations where a system has been perturbed by an external intervention. The ability to reliably make such causal predictions is of great value for practical applications in a variety of disciplines. Over the last two decades, remarkable progress has been made in the field. However, even though state-of-the-art causal inference algorithms work well on simulated data when all their assumptions are met, there is still a considerable gap between theory and practice. The goal of CAFES is to bridge that gap by developing theory and algorithms that will enable large-scale applications of causal inference in various challenging domains in science, industry and decision making. The key challenge that will be addressed is how to deal with cyclic causal relationships ("feedback loops"). Feedback loops are very common in many domains (e.g., biology, economy and climatology), but have mostly been ignored so far in the field. Building on recently established connections between dynamical systems and causal models, CAFES will develop theory and algorithms for causal modeling, reasoning, discovery and prediction for cyclic causal systems. Extensions to stationary and non-stationary processes will be developed to advance the state-of-the-art in causal analysis of time-series data. In order to optimally use available resources, computationally efficient and statistically robust algorithms for causal inference from observational and interventional data in the context of confounders and feedback will be developed. The work will be done with a strong focus on applications in molecular biology, one of the most promising areas for automated causal inference from data.

1 405 652 €

Start date: 2015-09-01, End date: 2020-08-31

Computer-generated imagery is now ubiquitous in our society, spanning fields such as games and movies, architecture, engineering, or virtual prototyping, while also helping create novel ones such as computational materials. With the increase in computational power and the improvement of acquisition techniques, there has been a paradigm shift in the field towards data-driven techniques, which has yielded an unprecedented level of realism in visual appearance. Unfortunately, this leads to a series of problems, identified in this proposal: First, there is a disconnect between the mathematical representation of the data and any meaningful parameters that humans understand; the captured data is machine-friendly, but not human friendly. Second, the many different acquisition systems lead to heterogeneous formats and very large datasets. And third, real-world appearance functions are usually nonlinear and high-dimensional. As a result, visual appearance datasets are increasingly unfit to editing operations, which limits the creative process for scientists, engineers, artists and practitioners in general. There is an immense gap between the complexity, realism and richness of the captured data, and the flexibility to edit such data. We believe that the current research path leads to a fragmented space of isolated solutions, each tailored to a particular dataset and problem. We propose a research plan at the theoretical, algorithmic and application levels, putting the user at the core. We will learn key relevant appearance features in terms humans understand, from which intuitive, predictable editing spaces, algorithms, and workflows will be defined. In order to ensure usability and foster creativity, we will also extend our research to efficient simulation of visual appearance, exploiting the extra dimensionality of the captured datasets. Achieving our goals will finally enable us to reach the true potential of real-world captured datasets in many aspects of society.

1 629 519 €

Start date: 2016-11-01, End date: 2021-10-31

How animal communication systems evolve is a fundamental question in ecology and evolution and crucial for our understanding of adaptation and speciation. I will make use of the process of urbanization to address how communication signals adapt to changes in the sensory environment. I will focus on the impact of noise and light pollution on acoustic communication of Neotropical frogs and address the following questions: 1) How do senders, such as a male frog, adjust their signals to altered sensory environments? I will assess plasticity and heritability of signal divergence found between urban and forest populations of the tungara frog. 2) How do signals evolve in response to direct (via sender) and indirect (via receivers) selection pressures? I will expose forest sites to noise and light pollution, parse out importance of multiple selection pressures and carry out experimental evolution using artificial phenotypes. 3) What are the evolutionary consequences of signal divergence? I will assess inter-and-intra sexual responses to signal divergence between urban and forest populations. 4) Can we predict how species adapt their signals to the sensory environment? I will use a trait-based comparative approach to study signal divergence among closely related species with known urban populations. Our state-of-the-art automated sender-receiver system allows for experimental evolution using long-lived species and opens new ways to study selection pressures operating on animal behaviour under real field conditions. Our expected results will provide crucial insight into the early stages of signal divergence that may ultimately lead to reproductive isolation and speciation.

1 500 000 €

Start date: 2019-01-01, End date: 2023-12-31

Familial forms of neurodegenerative diseases are caused by mutations in a single gene. It is unknown whether distinct mutations in the same gene or in functionally related genes cause disease through similar or disparate mechanisms. Furthermore, the precise molecular mechanisms underlying virtually all neurodegenerative disorders are poorly understood, and effective treatments are typically lacking. This is also the case for Charcot-Marie-Tooth (CMT) peripheral neuropathy caused by mutations in five distinct tRNA synthetase (aaRS) genes. We previously generated Drosophila CMT-aaRS models and used a novel method for cell-type-specific labeling of newly synthesized proteins in vivo to show that impaired protein translation may represent a common pathogenic mechanism. In this proposal, I aim to determine whether translation is also inhibited in CMT-aaRS mouse models, and whether all mutations cause disease through gain-of-toxic-function, or alternatively, whether some mutations act through a dominant-negative mechanism. In addition, I will evaluate whether all CMT-aaRS mutant proteins inhibit translation, and I will test the hypothesis, raised by our unpublished preliminary data shown here, that a defect in the transfer of the (aminoacylated) tRNA from the mutant synthetase to elongation factor eEF1A is the molecular mechanism underlying CMT-aaRS. Finally, I will validate the identified molecular mechanism in CMT-aaRS mouse models, as the most disease-relevant mammalian model. I expect to elucidate whether all CMT-aaRS mutations cause disease through a common molecular mechanism that involves inhibition of translation. This is of key importance from a therapeutic perspective, as a common pathogenic mechanism allows for a unified therapeutic approach. Furthermore, this proposal has the potential to unravel the detailed molecular mechanism underlying CMT-aaRS, what would constitute a breakthrough and a requirement for rational drug design for this incurable disease.

2 000 000 €

Start date: 2018-06-01, End date: 2023-05-31

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

The basal ganglia consist of a set of neuroanatomical structures that participate in the representation and execution of action sequences. Dopamine neurotransmission in the striatum, the main input nucleus of the basal ganglia, is a fundamental mechanism involved in learning and regulation of such actions. The striatum has multiple functional units, where the limbic striatum is thought to mediate motivational aspects of actions (e.g., goal-directedness) and the sensorimotor striatum their automation (e.g., habit formation). A long-standing question in the field is how limbic and sensorimotor domains communicate with each other, and specifically if they do so during the automation of action sequences. It has been suggested that such coordination is implemented by reciprocal loop connections between striatal projection neurons and the dopaminergic midbrain. Although very influential in theory the effectiveness of this limbic-sensorimotor “bridging” principle has yet to be verified. I hypothesize that during the automation of behaviour regional dopamine signalling is governed by a striatal hierarchy and that dysregulation of this coordination leads to compulsive execution of automatic actions characteristic of several psychiatric disorders. To test this hypothesis, we will conduct electrochemical measurements with real-time resolution simultaneously in limbic and sensorimotor striatum to assess the regional coordination of dopamine release in behaving animals. We developed novel chronically implantable electrodes to enable monitoring of dopamine dynamics throughout the development of habitual behaviour and its compulsive execution in transgenic rats - a species suitable for our complex behavioural assays. Novel rabies virus-mediated gene delivery for in vivo optogenetics in these rats will give us the unique opportunity to test whether specific loop pathways govern striatal dopamine transmission and are causally involved in habit formation and compulsive behaviour.

1 500 000 €

Start date: 2015-05-01, End date: 2020-04-30

The perfect execution of a voluntary movement requires the appropriate integration of current bodily state, sensory input and desired outcome. To assure that this motor output becomes and remains appropriate, the brain needs to learn from the result of previous outputs. The cerebellum plays a central role in sensorimotor integration, yet -despite decades of studies- there is no generally excepted theory for cerebellar functioning. I recently demonstrated that cerebellar modules, identified based on anatomical connectivity and gene expression, differ distinctly in spike activity properties. It is my long-term goal to identify the ontogeny of anatomical and physiological differences between modules, and their functional consequences. My hypothesis is that these differences can explain existing controversies, and unify contradicting results into one central theory. To this end, I have designed three key objectives. First, I will identify the development of connectivity and activity patterns at the input stage of the cerebellar cortex in relation to the cerebellar modules (key objective A). Next, I will relate the differences in gene expression levels between modules to differences in basal activity and strength of plasticity mechanisms in juvenile mice (key objective B). Finally, I will determine how module specific output develops in relation to behavior and what the effect of module specific mutations is on cerebellum-dependent motor tasks and higher order functions (key objective C). Ultimately, the combined results of all key objectives will reveal how distinct difference between cerebellar modules develop, and how this ensemble ensures proper cerebellar information processing for optimal coordination of timing and force of movements. Combined with the growing body of evidence for a cerebellar role in higher order brain functions and neurodevelopmental disorders, a unifying theory would be fundamental for understanding how the juvenile brain develops.

1 500 000 €

Start date: 2016-06-01, End date: 2021-05-31

In economics, a distinction is made between statistical and taste-based discrimination (henceforth, TBD). Statistical discrimination refers to discrimination in a context with strategic uncertainty. Someone who is uncertain about the future behaviour of a person with a different ethnicity may rely on information about the different ethnic group to which this person belongs to form beliefs about the behaviour of that person. This may lead to discrimination. TBD refers to discrimination in a context without strategic uncertainty. It implies suffering a disutility when interacting with ‘different’ others. This project systematically studies TBD in ethnically diverse societies. Identifying TBD is important because overcoming it requires different policies than overcoming statistical discrimination: they should deal with changing preferences of people rather than providing information about specific interaction partners. But identifying TBD is tricky. First, it is impossible to identify using uncontrolled empirical data because these data are characterised by strategic uncertainty. Second, people are generally reluctant to identify themselves as a discriminator. In the project, I study TBS using novel economic experiments that circumvent these problems. The project consists of three main objectives. First, I investigate whether and how preferences of European natives in social interactions depend on others’ ethnicity. Are natives as altruistic, reciprocal, envious to immigrants as compared to other natives? Second, I study whether natives have different fairness ideals—what constitutes a fair distribution of resources from the perspective of an impartial spectator—when it comes to natives than when it comes to non-natives. Third, I analyse whether preferences and fairness ideals depend on exposure to diversity: do preferences and fairness ideals of natives change as contact with non-natives increases, and, if so, how?

1 499 046 €

Start date: 2018-01-01, End date: 2022-12-31

In today’s globalized world, labor mobility is at the core of the political debate and a centerpiece for economic policy. The design of migration policies, such as selective, skill-biased, immigration policies, policies to encourage the integration of immigrants, or ones that facilitate geographical mobility to increase labor market opportunities of disadvantaged workers, requires a good understanding of a more fundamental issue: understanding the role of internal migration and immigration in shaping the career paths and human capital accumulation of workers. This project aims at providing a coherent analysis that allows us to understand the interactions between labor mobility and human capital accumulation, and their implications for economic policy design. This project focuses on three main issues: labor mobility, labor market effects of immigration, and the interaction between the two. Our questions are: (a) What are the role of temporary and permanent contracts in shaping career paths and geographic mobility of workers? (b) Does the forgone human capital accumulation during a recession produce a lost generation? Is this alleviated by geographical mobility? (c) What is the role of geographical and occupational mobility in spreading or containing the effects of technological progress on wage inequality? (d) To what extent selective immigration policies maximize native workers’ prospects and wellbeing? (e) How can we increase degree of assimilation of immigrants? To address these questions, we will develop dynamic equilibrium models that explicitly characterize human capital accumulation decisions of workers and how these decisions interact with migration. Our proposed models will introduce rich labor market structures and a variety of economic shocks. They will require the implementation of novel estimation methods, which we will also develop. The estimated models will be used to evaluate and design key economic policies for the labor market.

1 400 250 €

Start date: 2018-11-01, End date: 2023-10-31

The world is seasonal and organisms’ adjustment of their seasonal timing to this environmental variation is crucial for their fitness. Climate change is strongly impacting seasonal timing which makes a better understanding of the potential for micro-evolution of timing in natural populations essential. As any phenotypic change ultimately involves changes in the physiological mechanism underlying timing, we need to unravel the genetics of these mechanisms. I will carry out a highly integrated eco-evo-devo project on the causes and consequences of genetic variation in timing of reproduction in great tits (Parus major), an ecological model species for that we recently developed state-of-the-art genomic tools. I will develop a powerful instrument to study this timing mechanism by creating selection lines of early and late reproducing birds using genome-wide, rather than phenotypic, selection. The phenotypic response of selection lines birds will be assessed both in controlled environment aviaries and in birds introduced to the wild. To unravel how selection has altered the birds’ physiology I will measure key components of the physiological mechanism at the central, peripheral and egg production levels. As a unique next step I will then introduce selection line birds into a wild population to assess the fitness of these extreme phenotypes. This will enable me, for the first time, to estimate the selection on timing without confounds, which I will compare with traditional estimates using observational data. Finally, I will integrate genetics, physiology and ecology to hindcast the rate of genetic change in our wild population and validate this rate using DNA sampled over a 20-year period. This innovative project integrates state of the art developments in ecology, genetics and physiology (eco-evo-devo) will set new standards for future studies in other wild species and will be of key importance for our predictions of evolutionary responses to a warming world.

2 495 808 €

Start date: 2014-01-01, End date: 2018-12-31

Multicore processors are present nowadays in most digital devices, from smartphones to high-performance servers. The increasing computational power of these processors is essential for enabling many important emerging application domains such as big-data, media, medical, or scientific modeling. A fundamental technique to improve performance is speculation, a technique that consists in executing work before it is known if it is actually needed. In hardware, speculation significantly increases energy consumption by performing unnecessary operations, while speculation in software (e.g., compilers) is not the default thus preventing performance optimizations. Since performance in current multicores is limited by their power budget, it is imperative to make multicores as energy-efficient as possible to increase performance even further. In a multicore architecture, the cache coherence protocol is an essential component since its unique but challenging role is to offer a simple and unified view of the memory hierarchy. This project envisions that extending the role of the coherence protocol to simplify other system components will be the key to overcome the performance and energy limitations of current multicores. In particular, ECHO proposes to add simple but effective extensions to the cache coherence protocol in order to (i) reduce and even eliminate misspeculations at the processing cores and synchronization mechanisms and to (ii) enable speculative optimizations at compile time. The goal of this innovative approach is to improve the performance and energy efficiency of future multicore architectures. To accomplish the objectives proposed in this project, I will build on my 14 years expertise in cache coherence, documented in over 40 publications of high impact.

1 999 955 €

Start date: 2019-09-01, End date: 2024-08-31

Classical theory on community ecology models dynamics as interplay between top-down and bottom-up effects of population abundances only and considers population composition irrelevant. It ignores food-dependent ontogenetic development, in particular somatic growth, which characterizes most species and uniquely distinguishes organisms from fundamental units in physical or chemical multi-particle systems. Similarly, evolutionary theory has ignored the potential population feedback on food-dependent ontogenetic development. Classic theory has been shown to apply in case of ontogenetic symmetry in energetics, when dynamics of population abundance and composition are independent. Ontogenetic symmetry stipulates that mass-specific rates of net biomass turnover are independent of individual body size. Ontogenetic symmetry only represents a limiting, structurally unstable case, separating two stable domains with ontogenetic asymmetry in energetics, when either juveniles or adults have higher mass-specific net-biomass production. In case of ontogenetic asymmetry the dynamics of population abundance and composition become intimately linked, ultimately resulting in the emergence of positive feedbacks between densities of predators and their main prey. This transforms consumer-resource interactions into indivisible units, whose behavior can no longer be predicted from its constituting parts (the species). Ontogenetic asymmetry in energetics is thus a potent driver of self-organization in ecological communities. This research project aims at unraveling the eco-evolutionary dynamics of ontogenetic asymmetry in energetics, focusing on (1) the likelihood that ontogenetic asymmetry in energetics evolves as mechanism of self-organization in ecological communities, (2) the conditions that may have promoted or inhibited this evolution and (3) the extent to which ontogenetic asymmetry in energetics has contributed to the diversity of life and the development of complex life cycles.

1 779 634 €

Start date: 2013-06-01, End date: 2018-05-31

DSGE models are the standard tool of quantitative macroeconomics. We use them to measure economics phenomena and to provide policy advice. However, since Kydland and Prescott s 1982, the profession has fought about how to take these models to the data. Kydland and Prescott proposed to calibrate their model. Why? Macroeconomists could not compute their models efficiently. Moreover, the techniques required for estimating DSGE models using the likelihood did not exist. Finally, models were ranked very badly by likelihood ratio tests. Calibration offered a temporary solution. By focusing only on a very limited set of moments of the model, researchers could claim partial success and keep developing their theory. The landscape changed in the 1990s. There were developments along three fronts. First, macroeconomists learned how to efficiently compute equilibrium models with rich dynamics. Second, statisticians developed simulation techniques like Markov chain Monte Carlo (MCMC), which we require to estimate DSGE models. Third, and perhaps most important, computer power has become so cheap that we can now do things that were unthinkable 20 years ago. This proposal tries to estimate non-linear and/or non-normal DSGE models using a likelihood approach. Why non-linear models? Previous research has proved that second order approximation errors in the policy function have first order effects on the likelihood function. Why non-normal models? Time-varying volatility is key to understanding the Great Moderation. Kim and Nelson (1999), McConnell and Pérez-Quirós (2000), and Stock and Watson (2002) have documented a decline in the variance of output growth since the mid 1980s. Only DSGE models with richer structure than normal innovations can account for this.

909 942 €

Start date: 2010-07-01, End date: 2015-06-30

The fight against climate change is among Europe’s top policy priorities. In this research agenda, I propose to push out the frontier in the area of Energy and Environmental Economics by carrying out policy-relevant research on a pressing issue: how to design optimal regulatory and market-based solutions to achieve a least cost transition towards a low-carbon economy. The European experience provides unique natural experiments with which to test some of the most contentious issues that arise in the context of electricity markets, including the potential to change households’ demand patterns through dynamic pricing, the scope of renewables to mitigate market power and depress wholesale market prices, and the design and performance of the auctions for renewable support. While there is a body of policy work on these issues, it generally does not meet the required research standards. In this research, I will rely on cutting-edge theoretical, empirical, and simulation tools to disentangle these topics, while providing key economic insights that are relevant beyond electricity markets. On the theory front, I propose to develop new models that incorporate the intermittency of renewables to characterize optimal bidding as a key, broadly omitted ingredient in previous analysis. In turn, these models will provide a rigorous structure for the empirical and simulation analysis, which will rely both on traditional econometrics for casual inference as well as on state-of-the-art machine learning methods to construct counterfactual scenarios for policy analysis. While my focus is on energy and environmental issues, my research will also provide methodological contributions for other areas - particularly those related to policy design and policy evaluation. The conclusions of this research should prove valuable for academics, as well as to policy makers to assess the impact of environmental and energy policies and redefine them where necessary.

1 422 375 €

Start date: 2018-09-01, End date: 2023-08-31

Modern economic research emphasizes heterogeneity in various dimensions, such as individual preferences or firms’ technology. From an empirical perspective, the presence of unobserved heterogeneity (to the econometrician) creates challenging identification and estimation problems. In this proposal we explore these issues in a context where repeated observations are available for the same individual, and the researcher disposes of panel data. Most research to date adopts either of three approaches. One approach consists in modeling the distribution of unobserved heterogeneity, following a random-effects perspective (Chamberlain, 1984). Another approach looks for clever model-specific ways of differencing out the unobserved heterogeneity (Andersen, 1970, Honore and Kyriazidou, 2000). A more recent line of research relies on approximations that become more accurate when the number of observations per individual T gets large (Arellano and Hahn, 2006). Here we consider situations where T may be small, and the researcher does not restrict the distribution of the unobserved fixed effects. We will propose a new functional differencing approach which differences out the probability distribution of unobserved heterogeneity. This approach will generally be applicable in models with continuous dependent variables, emphasizing a possibility of point-identification of the structural parameters in those models. When outcomes are discrete, we will propose a nonlinear differencing strategy that delivers useful bounds on parameters in the presence of partial identification (Honore and Tamer, 2006).

1 410 000 €

Start date: 2010-12-01, End date: 2015-11-30

The main scientific contribution of this project will be a breakthrough in the understanding of cryptanalytic and side channel attacks of symmetric cryptosystems. We will do this by a unification of attacks that will a stepping stone to the holy grail of symmetric cryptography: provable security of concrete cryptosystems. The main real-world impact is that we will build cryptosystems that are much more efficient than those used today while having the same strength. Depending on the platform, higher efficiency translates to lower energy/power (in-body sensors, contactless payment cards etc.), but also lower latency (authentication for e.g car brakes or airbags) and/or lower heat dissipation (on-the-fly encryption of high bandwidth data streams). In a software implementation it simply means less CPU cycles per byte. We build our cryptosystems as modes, on top of block ciphers or permutations. For these primitives we adopt the classical technique of iterating a simple round function (more rounds means more security but less efficiency). We focus on round functions of algebraic degree 2. Their relative simplicity will allow a unification of all cryptanalytic attacks that exploit propagation of affine varieties and polynomial ideals (their dual) through the rounds and to precisely estimate their success rates. Moreover, we will design modes that strongly restrict the exposure of the primitive(s) to attackers and that permit security reductions to specific properties of the underlying primitive(s) in a formally verifiable way. In comparison to the classical pseudorandom and ideal permutation models, this will allow reducing the number of rounds while preserving security with high assurance. We will also study side channel attacks of our round functions and ways to defend against them. We will make ASIC prototypes and implement novel efficient countermeasures against side channel attacks and use this to evaluate their effectiveness in practice.

2 500 000 €

Start date: 2018-10-01, End date: 2023-09-30