ERC FUNDED PROJECTS

During the 20th century computer technology evolved from bulky, slow, special purpose mechanical engines to the now ubiquitous silicon chips and software that are one of the pinnacles of human ingenuity. The goal of the field of molecular programming is to take the next leap and build a new generation of matter-based computers using DNA, RNA and proteins. This will be accomplished by computer scientists, physicists and chemists designing molecules to execute ``wet'' nanoscale programs in test tubes. The workflow includes proposing theoretical models, mathematically proving their computational properties, physical modelling and implementation in the wet-lab. The past decade has seen remarkable progress at building static 2D and 3D DNA nanostructures. However, unlike biological macromolecules and complexes that are built via specified self-assembly pathways, that execute robotic-like movements, and that undergo evolution, the activity of human-engineered nanostructures is severely limited. We will need sophisticated algorithmic ideas to build structures that rival active living systems. Active-DNA, aims to address this challenge by achieving a number of objectives on computation, DNA-based self-assembly and molecular robotics. Active-DNA research work will range from defining models and proving theorems that characterise the computational and expressive capabilities of such active programmable materials to experimental work implementing active DNA nanostructures in the wet-lab.

2 349 603 €

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

Rates of domestic violence and the relative risk of premature death for women are higher in sub-Saharan Africa than in any other region. Yet we know remarkably little about the economic forces, incentives and constraints that drive discrimination against women in this region, making it hard to identify policy levers to address the problem. This project will help fill this gap. I will investigate gender discrimination from two complementary perspectives. First, through the lens of economic history, I will investigate the forces driving trends in women’s relative well-being since slavery. To quantify the evolution of well-being of sub-Saharan women relative to men, I will use three types of historical data: anthropometric indicators (relative height), vital statistics (to compute numbers of missing women), and outcomes of formal and informal family law disputes. I will then investigate how major economic developments and changes in family laws differentially affected women’s welfare across ethnic groups with different norms on women’s roles and rights. Second, using intra-household economic models, I will provide new insights into domestic violence and gender bias in access to crucial resources in present-day Africa. I will develop a new household model that incorporates gender identity and endogenous outside options to explore the relationship between women’s empowerment and the use of violence. Using the notion of strategic delegation, I will propose a new rationale for the separation of budgets often observed in African households and generate predictions of how improvements in women’s outside options affect welfare. Finally, with first hand data, I will investigate intra-household differences in nutrition and work effort in times of food shortage from the points of view of efficiency and equity. I will use activity trackers as an innovative means of collecting high quality data on work effort and thus overcome data limitations restricting the existing literature

1 499 313 €

Start date: 2018-08-01, End date: 2023-07-31

Real-world optimization problems pose major challenges to algorithmic research. For instance, (i) many important problems are believed to be intractable (i.e. NP-hard) and (ii) with the growth of data size, modern applications often require a decision making under {\em incomplete and dynamically changing input data}. After several decades of research, central problems in these domains have remained poorly understood (e.g. Is there an asymptotically most efficient binary search trees?) Existing algorithmic techniques either reach their limitation or are inherently tailored to special cases. This project attempts to untangle this gap in the state of the art and seeks new interplay across multiple areas of algorithms, such as approximation algorithms, online algorithms, fixed-parameter tractable (FPT) algorithms, exponential time algorithms, and data structures. We propose new directions from the {\em structural perspectives} that connect the aforementioned algorithmic problems to basic questions in combinatorics. Our approaches fall into one of the three broad schemes: (i) new structural theory, (ii) intermediate problems, and (iii) transfer of techniques. These directions partially build on the PI's successes in resolving more than ten classical problems in this context. Resolving the proposed problems will likely revolutionize our understanding about algorithms and data structures and potentially unify techniques in multiple algorithmic regimes. Any progress is, in fact, already a significant contribution to the algorithms community. We suggest concrete intermediate goals that are of independent interest and have lower risks, so they are suitable for Ph.D students.

1 411 258 €

Start date: 2018-02-01, End date: 2023-01-31

Online markets currently form an important share of the global economy. The Internet hosts classical markets (real-estate, stocks, e-commerce) as well allowing new markets with previously unknown features (web-based advertisement, viral marketing, digital goods, crowdsourcing, sharing economy). Algorithms play a central role in many decision processes involved in online markets. For example, algorithms run electronic auctions, trade stocks, adjusts prices dynamically, and harvest big data to provide economic information. Thus, it is of paramount importance to understand the algorithmic and mechanism design foundations of online markets. The algorithmic research issues that we consider involve algorithmic mechanism design, online and approximation algorithms, modelling uncertainty in online market design, and large-scale data analysisonline and approximation algorithms, large-scale optimization and data mining. The aim of this research project is to combine these fields to consider research questions that are central for today's Internet economy. We plan to apply these techniques so as to solve fundamental algorithmic problems motivated by web-basedInternet advertisement, Internet market designsharing economy, and crowdsourcingonline labour marketplaces. While my planned research is focussedcentered on foundational work with rigorous design and analysis of in algorithms and mechanismsic design and analysis, it will also include as an important component empirical validation on large-scale real-life datasets.

1 780 150 €

Start date: 2018-07-01, End date: 2023-06-30

"During the past twenty years, we have witnessed profound technological changes, summarised under the terms of digital revolution or entering the information age. It is evident that these technological changes will have a deep societal impact, and questions of privacy and security are primordial to ensure the survival of a free and open society. Cryptology is a main building block of any security solution, and at the heart of projects such as electronic identity and health cards, access control, digital content distribution or electronic voting, to mention only a few important applications. During the past decades, public-key cryptology has established itself as a research topic in computer science; tools of theoretical computer science are employed to “prove” the security of cryptographic primitives such as encryption or digital signatures and of more complex protocols. It is often forgotten, however, that all practically relevant public-key cryptosystems are rooted in pure mathematics, in particular, number theory and arithmetic geometry. In fact, the socalled security “proofs” are all conditional to the algorithmic untractability of certain number theoretic problems, such as factorisation of large integers or discrete logarithms in algebraic curves. Unfortunately, there is a large cultural gap between computer scientists using a black-box security reduction to a supposedly hard problem in algorithmic number theory and number theorists, who are often interested in solving small and easy instances of the same problem. The theoretical grounds on which current algorithmic number theory operates are actually rather shaky, and cryptologists are generally unaware of this fact. The central goal of ANTICS is to rebuild algorithmic number theory on the firm grounds of theoretical computer science."

1 453 507 €

Start date: 2012-01-01, End date: 2016-12-31

With the prevalence of mobile computing devices and the increasing availability of pervasive services, ubiquitous computing (Ubicomp) is a reality for many people. This reality is generating opportunities for people to interact socially in new and richer ways, and to work more effectively in a variety of new environments. More generally, Ubicomp infrastructures – controlled by software – will determine users’ access to critical services. With these opportunities come higher risks of misuse by malicious agents. Therefore, the role and design of software for managing use and protecting against misuse is critical, and the engineering of software that is both functionally effective while safe guarding user assets from harm is a key challenge. Indeed the very nature of Ubicomp means that software must adapt to the changing needs of users and their environment, and, more critically, to the different threats to users’ security and privacy. ASAP proposes to radically re-conceptualise software engineering for Ubicomp in ways that are cognisant of the changing functional needs of users, of the changing threats to user assets, and of the changing relationships between them. We propose to deliver adaptive software capabilities for supporting users in managing their privacy requirements, and adaptive software capabilities to deliver secure software that underpin those requirements. A key novelty of our approach is its holistic treatment of security and human behaviour. To achieve this, it draws upon contributions from requirements engineering, security & privacy engineering, and human-computer interaction. Our aim is to contribute to software engineering that empowers and protects Ubicomp users. Underpinning our approach will be the development of representations of security and privacy problem structures that capture user requirements, the context in which those requirements arise, and the adaptive software that aims to meet those requirements.

2 499 041 €

Start date: 2012-10-01, End date: 2018-09-30

The Milky Way is a complex system, with dynamical and chemical substructures, where several competing processes such as mergers, internal secular evolution, gas accretion and gas flows take place. To study in detail how such a giant spiral galaxy was formed and evolved, we need to reconstruct the sequence of its main formation events with high (~10%) temporal resolution. Asterochronometry will determine accurate, precise ages for tens of thousands of stars in the Galaxy. We will take an approach distinguished by a number of key aspects including, developing novel star-dating methods that fully utilise the potential of individual pulsation modes, coupled with a careful appraisal of systematic uncertainties on age deriving from our limited understanding of stellar physics. We will then capitalise on opportunities provided by the timely availability of astrometric, spectroscopic, and asteroseismic data to build and data-mine chrono-chemo-dynamical maps of regions of the Milky Way probed by the space missions CoRoT, Kepler, K2, and TESS. We will quantify, by comparison with predictions of chemodynamical models, the relative importance of various processes which play a role in shaping the Galaxy, for example mergers and dynamical processes. We will use chrono-chemical tagging to look for evidence of aggregates, and precise and accurate ages to reconstruct the early star formation history of the Milky Way’s main constituents. The Asterochronometry project will also provide stringent observational tests of stellar structure and answer some of the long-standing open questions in stellar modelling (e.g. efficiency of transport processes, mass loss on the giant branch, the occurrence of products of coalescence / mass exchange). These tests will improve our ability to determine stellar ages and chemical yields, with wide impact e.g. on the characterisation and ensemble studies of exoplanets, on evolutionary population synthesis, integrated colours and thus ages of galaxies.

1 958 863 €

Start date: 2018-04-01, End date: 2023-03-31

Cosmic Rays (ionized atomic nuclei) are the only matter from beyond our solar system or even from extragalactic space, that we can directly investigate. Up to energies of 10^17 eV they most likely originate in our Galaxy. The highest-energy cosmic rays (>10^18 eV) cannot be magnetically bound any more to the Galaxy and are most likely of extragalactic origin. The pure existence of these particles raises the question about their origin – how and where are they accelerated? How do they propagate through the universe and interact? How can we directly probe extragalactic matter and how can we locate its origin? A key to understand the origin of cosmic rays is to measure the particle species (atomic mass). A precise mass measurement will allow discriminating astrophysical models and will clarify the reason for the observed suppression of the cosmic-ray flux at the highest energies, namely the maximum energy of the accelerators or the energy losses during propagation. I address these questions by employing a new technique to precisely measure the cosmic-ray mass composition, which my group pioneered, the radio detection of air showers (induced by high-energy cosmic rays in the atmosphere) on very large scales, detecting horizontal air showers with zenith angles from 60° to 90°. The new set-up will be the world-largest radio array, operated together with the well-established Auger surface and fluorescence detectors, forming a unique set-up to measure the properties of cosmic rays with unprecedented precision for energies above 10^17.5 eV. The radio technique is a cost-effective and robust method to measure the cosmic-ray energy and mass, complementary to established techniques. The energy scale of the radio measurements is established from first principles. The proposed detectors will also enhance the detection capabilities for high-energy neutrinos and the search for new physics through precision measurements of the electromagnetic and muonic shower components.

3 499 249 €

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

The standard model of cosmology, the ɅCDM model, is remarkably successful at explaining a wide range of observations of our Universe. However, it is now being subjected to much more stringent tests than ever before, and recent large-scale structure (LSS) measurements appear to be in tension with its predictions. Is this tension signalling that new physics is required? For example, time-varying dark energy, or perhaps a modified theory of gravity? A contribution from massive neutrinos? Before coming to such bold conclusions we must be certain that all of the important systematic errors in the LSS tests have been accounted for. Presently, the largest source of systematic uncertainty is from the modelling of complicated astrophysical phenomena associated with galaxy formation. In particular, energetic feedback processes associated with star formation and black hole growth can heat and expel gas from collapsed structures and modify the large-scale distribution of matter. Furthermore, the LSS field is presently separated into many sub-fields (each using different models, that usually neglect feedback), preventing a coherent analysis. Cosmological hydrodynamical simulations (are the only method which) can follow all the relevant matter components and self-consistently capture the effects of feedback. I have been leading the development of large-scale simulations with physically-motivated prescriptions for feedback that are unrivalled in their ability to reproduce the observed properties of massive systems. With ERC support, I will build a team to exploit these developments, to produce a suite of simulations designed specifically for LSS cosmology applications with the effects of feedback realistically accounted for and which will allow us to unite the different LSS tests. My team and I will make the first self-consistent comparisons with the full range of LSS cosmology tests, and critically assess the evidence for physics beyond the standard model.

1 725 982 €

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

BEACON aims at performing an ambitious multi-disciplinary (optical, radio astronomy and theoretical physics) study to enable a fundamentally improved understanding of gravitation and space-time. For almost a century Einstein's general relativity has been the last word on gravity. However, superstring theory predicts new gravitational phenomena beyond relativity. In this proposal I will attempt to detect these new phenomena, with a sensitivity 20 times better than state-of-the-art attempts. A successful detection would take physics beyond its current understanding of the Universe. These new gravitational phenomena are emission of dipolar gravitational waves and the violation of the strong equivalence principle (SEP). I plan to look for them by timing newly discovered binary pulsars. I will improve upon the best current limits on dipolar gravitational wave emission by a factor of 20 within the time of this proposal. I also plan to develop a test of the Strong Equivalence Principle using a new pulsar/main-sequence star binary. The precision of this test is likely to surpass the current best limits within the time frame of this proposal and then keep improving indefinitely with time. This happens because this is the cleanest gravitational experiment ever carried out. In order to further these goals, I plan to build the ultimate pulsar observing system. By taking advantage of recent technological advances in microwave engineering (particularly sensitive ultra-wide band receivers) digital electronics (fast analogue-to-digital converters and digital spectrometers) and computing, my team and me will be able to greatly improve the sensitivity and precision for pulsar timing experiments and exploit the capabilities of modern radio telescopes to their limits. Pulsars are the beacons that will guide me in these new, uncharted seas.

1 892 376 €

Start date: 2011-09-01, End date: 2016-08-31

BEHAVFRICTIONS will use novel models focussing on information-processing frictions to explain choice patterns described in behavioral economics and psychology. The proposed research will provide microfoundations that are essential for (i) identification of stable preferences, (ii) counterfactual predictions, and (iii) normative conclusions. (i) Agents who face information-processing costs must trade the precision of choice against information costs. Their behavior thus reflects both their stable preferences and the context-dependent procedures that manage their errors stemming from imperfect information processing. In the absence of micro-founded models, the two drivers of the behavior are difficult to disentangle for outside observers. In some pillars of the proposal, the agents follow choice rules that closely resemble logit rules used in structural estimation. This will allow me to reinterpret the structural estimation fits to choice data and to make a distinction between the stable preferences and frictions. (ii) Such a distinction is important in counterfactual policy analysis because the second-best decision procedures that manage the errors in choice are affected by the analysed policy. Incorporation of the information-processing frictions into existing empirical methods will improve our ability to predict effects of the policies. (iii) My preliminary results suggest that when an agent is prone to committing errors, biases--such as overconfidence, confirmatory bias, or perception biases known from prospect theory--arise under second-best strategies. By providing the link between the agent's environment and the second-best distribution of the perception errors, my models will delineate environments in which these biases shield the agents from the most costly mistakes from environments in which the biases turn into maladaptations. The distinction will inform the normative debate on debiasing.

1 321 488 €

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

According to the European Commission, to design effective policies for ensuring a “more dynamic, innovative and competitive” economy, it is essential to understand the decision-making process of firms as they differ a lot in terms of their capacities and policy responses (EC 2007). The objective of my future research is to provide such an analysis. BIGlobal will examine the sources of firm growth and market power to provide new insights into welfare and policy in a globalized world. Much of analysis of the global economy is set in the paradigm of markets that allocate resources efficiently and there is little role for policy. But big firms dominate economic activity, especially across borders. How do firms grow and what is the effect of their market power on the welfare impact of globalization? This project will determine how firm decisions matter for the aggregate gains from globalization, the division of these gains across different individuals and their implications for policy design. Over the next five years, I will incorporate richer firms behaviour in models of international trade to understand how trade and industrial policies impact the growth process, especially in less developed markets. The specific questions I will address include: how can trade and competition policy ensure consumers benefit from globalization when firms engaged in international trade have market power, how do domestic policies to encourage agribusiness firms affect the extent to which small farmers gain from trade, how do industrial policies affect firm growth through input linkages, and what is the impact of banking globalization on the growth of firms in the real sector. Each project will combine theoretical work with rich data from developing economies to expand the frontier of knowledge on trade and industrial policy, and to provide a basis for informed policymaking.

1 313 103 €

Start date: 2017-12-01, End date: 2022-11-30

"The vast majority of research in computer security is dedicated to the design of detection, protection, and prevention solutions. While these techniques play a critical role to increase the security and privacy of our digital infrastructure, it is enough to look at the news to understand that it is not a matter of ""if"" a computer system will be compromised, but only a matter of ""when"". It is a well known fact that there is no 100% secure system, and that there is no practical way to prevent attackers with enough resources from breaking into sensitive targets. Therefore, it is extremely important to develop automated techniques to timely and precisely analyze computer security incidents and compromised systems. Unfortunately, the area of incident response received very little research attention, and it is still largely considered an art more than a science because of its lack of a proper theoretical and scientific background. The objective of BITCRUMBS is to rethink the Incident Response (IR) field from its foundations by proposing a more scientific and comprehensive approach to the analysis of compromised systems. BITCRUMBS will achieve this goal in three steps: (1) by introducing a new systematic approach to precisely measure the effectiveness and accuracy of IR techniques and their resilience to evasion and forgery; (2) by designing and implementing new automated techniques to cope with advanced threats and the analysis of IoT devices; and (3) by proposing a novel forensics-by-design development methodology and a set of guidelines for the design of future systems and software. To provide the right context for these new techniques and show the impact of the project in different fields and scenarios, BITCRUMBS plans to address its objectives using real case studies borrowed from two different domains: traditional computer software, and embedded systems. "

1 991 504 €

Start date: 2018-04-01, End date: 2023-03-31

I seek increasing our understanding of the origin of asset price booms and bust cycles and propose constructing structural dynamic equilibrium models that allow formalizing their interaction with the dynamics of consumption, hours worked, the current account, stock market trading activity, and monetary policy. For this purpose I propose developing macroeconomic models that relax the assumption of common knowledge of beliefs and preferences, incorporating instead subjective beliefs and learning about market behavior. These features allow for sustained deviations of asset prices from fundamentals in a setting where all agents behave individually rational. The first research project derives the derivative price implications of asset price models with learning agents and determines the limits to arbitrage required so that learning models are consistent with the existence of only weak incentives for improving forecasts and beliefs. The second project introduces housing, collateral constraints and open economy features into existing asset pricing models under learning to explain a range of cross-sectional facts about the behavior of the current account that have been observed in the recent housing boom and bust cycle. The third project constructs quantitatively plausible macro asset pricing models that can explain the dynamics of consumption and hours worked jointly with the occurrence of asset price boom and busts cycles. The forth project develops a set of monetary policy models allowing to study the interaction between monetary policies, the real economy and asset prices, and determines how monetary policy should optimally react to asset price movements. The last project explains the aggregate trading patterns on stock exchanges over boom and bust cycles and improves our understanding of the forces supporting the large cross-sectional heterogeneity in return expectations revealed in survey data.

769 440 €

Start date: 2011-09-01, End date: 2017-04-30

The constantly increasing number of attacks on web applications shows how their rapid development has not been accompanied by adequate security foundations and demonstrates the lack of solid security enforcement tools. Indeed, web applications expose a gigantic attack surface, which hinders a rigorous understanding and enforcement of security properties. Hence, despite the worthwhile efforts to design secure web applications, users for a while will be confronted with vulnerable, or maliciously crafted, code. Unfortunately, end users have no way at present to reliably protect themselves from malicious applications. BROWSEC will develop a holistic approach to client-side web security, laying its theoretical foundations and developing innovative security enforcement technologies. In particular, BROWSEC will deliver the first client-side tool to secure web applications that is practical, in that it is implemented as an extension and can thus be easily deployed at large, and also provably sound, i.e., backed up by machine-checked proofs that the tool provides end users with the required security guarantees. At the core of the proposal lies a novel monitoring technique, which treats the browser as a blackbox and intercepts its inputs and outputs in order to prevent dangerous information flows. With this lightweight monitoring approach, we aim at enforcing strong security properties without requiring any expensive and, given the dynamic nature of web applications, statically infeasible program analysis. BROWSEC is thus a multidisciplinary research effort, promising practical impact and delivering breakthrough advancements in various disciplines, such as web security, JavaScript semantics, software engineering, and program verification.

1 990 000 €

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

The proposed project will significantly improve the insight in the processes that have changed a comet nucleus or asteroid since their formation. These processes typically go along with activity, the observable release of gas and/or dust. Understanding the evolutionary processes of comets and asteroids will allow us to answer the crucial question which aspects of these present-day bodies still provide essential clues to their formation in the protoplanetary disc of the early solar system. Ground-breaking progress in understanding these fundamental questions can now be made thanks to the huge and unprecedented data set returned between 2014 and 2016 by the European Space Agency’s Rosetta mission to comet 67P/Churyumov-Gerasimenko, and by recent major advances in the observational study of active asteroids facilitated by the increased availability of sky surveys and follow-on observations with world-class telescopes. The key aims of this proposal are to - Obtain a unified quantitative picture of the different erosion processes active in comets and asteroids, - Investigate how ice is stored in comets and asteroids, - Characterize the ejected dust (size distribution, optical and thermal properties) and relate it to dust around other stars, - Understand in which respects comet 67P can be considered as representative of a wider sample of comets or even asteroids. We will follow a highly multi-disciplinary approach analyzing data from many Rosetta instruments, ground- and space-based telescopes, and connect these through numerical models of the dust dynamics and thermal properties.

1 484 688 €

Start date: 2018-03-01, End date: 2023-02-28

When interstellar clouds collapse to form new stars and planets, the surrounding gas and dust become part of the infalling envelopes and rotating disks, thus providing the basic material from which new solar systems are made. Instrumentation to probe the physics and chemistry in low-mass star-forming regions has so far lacked spatial resolution. I propose here an integrated observational-modeling-laboratory program to survey protostars and disks on the relevant scales of 1-50 AU where planet formation takes place. The observations are centered on new data coming from the Atacama Large Millimeter / submillimeter Array (ALMA), and the analysis includes unique new data from key programs on Herschel, Spitzer and VLT that I am (co-)leading. The combination of millimeter and infrared data allows the full range of temperatures from 10-2000 K in star- and planet- forming regions to be probed, for both gas and solids. The molecular line data are used as diagnostics of physical parameters (such as UV field, cosmic ray ionization rate, kinematics, mixing, shock strength, grain growth, gas/dust ratios) as well as to follow the chemistry of water and complex organic molecules from cores to disks, which ultimately may be delivered to terrestrial planets. The implications for the history of volatile material in our own solar systen and exo-planetary atmospheres will be assessed by comparing models and data with cometary taxonomy and, ultimately, feeding them into planet population synthesis models. Altogether, this program will bring the link between interstellar chemistry and solar system and exo-planetary research to a new level. The project will train four PhD students in a truly interdisciplinary environment in which they are exposed to all aspects of molecular astrophysics and have access to ample ALMA expertise, and it will prepare two postdocs for future faculty positions.

2 499 150 €

Start date: 2012-07-01, End date: 2018-06-30

A large social science literature tries to describe and understand the causes and consequences of crime, usually focusing on individuals’ criminal activity in isolation. The ambitious aim of this research project is to establish a broader perspective of crime that takes into account the social context in which it takes place. The findings will inform policymakers on how to better use funds both for crime prevention and the rehabilitation of incarcerated criminals. Criminal activity is often a group phenomenon, yet little is known about how criminal networks form and what can be done to break them up or prevent them from forming in the first place. Overlooking victims of crime and their relationships to criminals has led to an incomplete and distorted view of crime and its individual and social costs. While a better understanding of these social interactions is crucial for designing more effective anti-crime policy, existing research in criminology, sociology and economics has struggled to identify causal effects due to data limitations and difficult statistical identification issues. This project will push the research frontier by combining register datasets that have never been merged before, and by using several state-of-the-art statistical methods to estimate causal effects related to criminal peer groups and their victims. More specifically, we aim to do the following: -Use recent advances in network modelling to describe the structure and density of various criminal networks and study network dynamics following the arrest/incarceration or death of a central player in a network. -Obtain a more accurate measure of the societal costs of crime, including actual measures for lost earnings and physical and mental health problems, following victims and their offenders both before and after a crime takes place. -Conduct a randomized controlled trial within a prison system to better understand how current rehabilitation programs affect criminal and victim networks.

1 187 046 €

Start date: 2018-03-01, End date: 2023-02-28

The “Concurrency Made Easy” project is an attempt to achieve a conceptual breakthrough on the most daunting challenge in information technology today: mastering concurrency. Concurrency, once a specialized technique for experts, is forcing itself onto the entire IT community because of a disruptive phenomenon: the “end of Moore’s law as we know it”. Increases in performance can no longer happen through raw hardware speed, but only through concurrency, as in multicore architectures. Concurrency is also critical for networking, cloud computing and the progress of natural sciences. Software support for these advances lags, mired in concepts from the 1960s such as semaphores. Existing formal models are hard to apply in practice. Incremental progress is not sufficient; neither are techniques that place the burden on programmers, who cannot all be expected to become concurrency experts. The CME project attempts a major shift on the side of the supporting technology: languages, formal models, verification techniques. The core idea of the CME project is to make concurrency easy for programmers, by building on established ideas of modern programming methodology (object technology, Design by Contract) shifting the concurrency difficulties to the internals of the model and implementation. The project includes the following elements. 1. Sound conceptual model for concurrency. The starting point is the influential previous work of the PI: concepts of object-oriented design, particularly Design by Contract, and the SCOOP concurrency model. 2. Reference implementation, integrated into an IDE. 3. Performance analysis. 4. Theory and formal basis, including full semantics. 5. Proof techniques, compatible with proof techniques for the sequential part. 6. Complementary verification techniques such as concurrent testing. 7. Library of concurrency components and examples. 8. Publication, including a major textbook on concurrency.

2 482 957 €

Start date: 2012-04-01, End date: 2018-09-30

The last 20 years of rapid development in the computational-theoretic aspects of the fixed-language Constraint Satisfaction Problems (CSPs) has been fueled by a connection between the complexity and a certain concept capturing symmetry of computational problems in this class. My vision is that this connection will eventually evolve into the organizing principle of computational complexity and will lead to solutions of fundamental problems such as the Unique Games Conjecture or even the P-versus-NP problem. In order to break through the current limits of this algebraic approach, I will concentrate on specific goals designed to (A) discover suitable objects capturing symmetry that reflect the complexity in problem classes, where such an object is not known yet; (B) make the natural ordering of symmetries coarser so that it reflects the complexity more faithfully; (C) delineate the borderline between computationally hard and easy problems; (D) strengthen characterizations of existing borderlines to increase their usefulness as tools for proving hardness and designing efficient algorithm; and (E) design efficient algorithms based on direct and indirect uses of symmetries. The specific goals concern the fixed-language CSP over finite relational structures and its generalizations to infinite domains (iCSP) and weighted relations (vCSP), in which the algebraic theory is highly developed and the limitations are clearly visible. The approach is based on joining the forces of the universal algebraic methods in finite domains, model-theoretical and topological methods in the iCSP, and analytical and probabilistic methods in the vCSP. The starting point is to generalize and improve the Absorption Theory from finite domains.

1 211 375 €

Start date: 2018-02-01, End date: 2023-01-31

Many important social problems—from the workplace to climate change—require the cooperation of individuals in situations in which collective welfare is jeopardized by self-interest and contractual solutions that align collective and individual interest are not feasible. While this suggests a bleak outcome if people are selfish, recent research in the behavioural sciences suggests that rather than being selfish, many people are non-strategic ‘strong reciprocators’ who cooperate if others cooperate and who punish unfair behaviour even if such cooperation or punishment is individually costly. The fundamental importance of strong reciprocity is that is helps achieving cooperation in situations in which self-interest predicts its breakdown. The major ambition and innovation of this research programme is to “put strong reciprocity into context” by investigating how incentives, social and cultural context, and gender and personality differences, shape strong reciprocity and, as a consequence, cooperation. I propose four linked work packages, which all address key open questions of interest to economists and other behavioural scientists. First, I investigate how incentives influence strong reciprocity: Under which conditions do incentives undermine or enhance strong reciprocity and thereby cooperation? Second, I investigate how strong reciprocity relates to social norms of cooperation and is shaped by social context. Third, I use cross-cultural experiments to study the role of cultural influences on strong reciprocity and how culture interacts with incentive structures: when does culture matter for cooperation? Finally, I study personality and gender differences in strong reciprocity. All projects use economic experiments and insights from across the behavioural sciences. The overarching objective is to develop a ‘behavioural economics of cooperation’, that is, the basic science of relevant behavioural principles that are needed to achieve sustainable cooperation.

2 072 844 €

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

The standard model of cosmology is impressively consistent with a large number of observations. Its parameters have been determined with great accuracy with the Planck CMB (cosmic microwave background) mission. However, recently local determinations of the Hubble constant as well as ob- servations of strong and weak gravitational lensing have found some tension with Planck. Are those observations first glimpses at a crack in the standard model and hints of an evolving dark energy com- ponent? With this ERC Consolidator Grant I will answer these questions by greatly increasing the robustness of one of those cosmological probes, the weak lensing effect of the large scale structure of the Universe also called cosmic shear. In order to reach this goal I will concentrate on the largest outstanding source of systematic error: photometric redshifts (photo-z). I will exploit the unique combination of two European imaging surveys in the optical and infrared wavelength regime, an additional narrow-band imaging survey with extremely precise photo-z, and spectroscopic calibration data from a recently approved ESO large program on the VLT. Using angular cross-correlations and machine-learning I will calibrate the photo- z in a two-stage process making sure that this crucial systematic uncertainty will keep pace with the growing statistical power of imaging surveys. This will yield an uncertainty on the amplitude of the clustering of dark matter that is smaller than the best constraints from the CMB. I will also apply these methods to ESA’s Euclid mission launching in 2020, which will fail if photo-z are not better understood by then. If the discrepancy between lensing and CMB measurements holds this would potentially result in a revolution of our understanding of the Universe. Regardless of this spectacular short-term possibility I will turn cosmic shear – one of the most powerful cosmological probes of dark energy – into a litmus test for our cosmological paradigm.

1 931 493 €

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

The cost of software quality assurance (QA) dominates the cost of IT development and maintenance projects. QA is frequently on the critical path to market. Effective software QA is therefore decisive for the competitiveness of numerous industries that rely on IT, and essential for government tasks that rely heavily on IT. This research programme will provide a pragmatic solution to the most pressing issue in software QA in mainstream software engineering: the use of concurrency. Programmers make use of numerous favors of concurrency in order to achieve better scalability, savings in power, increase reliability, and to boost performance. The need for software that makes diligent use of concurrent computational resources has been exacerbated by power-efficient multi-core CPUs, which are now widely deployed, but still unfertilized due to the lack of appropriate software. Concurrent software is particularly difficult to test, as bugs depend on particular interlavings between the sequential computations. Defects are therefore difficult to reproduce and diagnose, and often elude even very experienced programmers. We propose to develop new, ground-braking reasoning and testing technology for this kind of software, with the goal of cutting the staff effort in QA of concurrent effort in half. We will use a tightly integrated combination of scalable and performant testing technology and Model Checking and abstract interpretation engines to prune the search. Every aspect of the research programme is geared towards improving the productivity of the average application programmer. Our theories and reasoning technology will therefore be implemented in a seamless fashion within the existing, well-accepted programming environments Visual Studio and Eclipse, in close collaboration with Microsoft and IBM.

1 368 355 €

Start date: 2011-12-01, End date: 2017-11-30

Computing is changing from living on our desktops and in dedicated devices to being everywhere. In phones, sensors, appliances, and robots – computers (from now on devices) are everywhere and affecting all aspects of our lives. The techniques to make them safe and reliable are investigated and are starting to emerge and consolidate. However, these techniques enable devices to work in isolation or co-exist. We currently do not have techniques that enable development of real autonomous collaboration between devices. Such techniques will revolutionize all usage of devices and, as consequence, our lives. Manufacturing, supply chain, transportation, infrastructures, and earth- and space exploration would all transform using techniques that enable development of collaborating devices. When considering isolated (and co-existing) devices, reactive synthesis – automatic production of plans from high level specification – is emerging as a viable tool for the development of robots and reactive software. This is especially important in the context of safety-critical systems, where assurances are required and systems need to have guarantees on performance. The techniques that are developed today to support robust, assured, reliable, and adaptive devices rely on a major change in focus of reactive synthesis. The revolution of correct-by-construction systems from specifications is occurring and is being pushed forward. However, to take this approach forward to work also for real collaboration between devices the theoretical frameworks that will enable distributed synthesis are required. Such foundations will enable the correct-by-construction revolution to unleash its potential and allow a multiplicative increase of utility by cooperative computation. d-SynMA will take distributed synthesis to this new frontier by considering novel interaction and communication concepts that would create an adaptable framework of correct-by-construction application of collaborating devices.

1 871 272 €

Start date: 2018-05-01, End date: 2023-04-30

Galaxy redshift surveys have been central in establishing the current successful cosmological model. Reconstructing the large-scale distribution of galaxies in space and time, they provide us with a unique probe of the basic constituents of the Universe, their evolution and the background fundamental physics. A new generation of even larger surveys is planned for the starting decade, with the aim of solving the remaining mysteries of the standard model using high-precision measurements of galaxy clustering. These entail the nature of the “dark sector” and in particular the origin of the accelerated cosmic expansion. While data accumulation already started, the needed analysis capabilities to reach the required percent levels in both accuracy and precision are not ready yet. I propose to establish a focused research group to develop these tools and optimally analyze the new data, while being directly involved in their collection. New techniques as redshift-space distortions and well-known but still debated probes as galaxy clusters will be refined to a new level. They will be combined with more standard methods as baryonic acoustic oscillations and external data as CMB anisotropies. Performances will be validated on mock samples from large numerical simulations and then applied to state-of-the-art data with enhanced control over systematic errors to obtain the best achievable measurements. These new capabilities will be decisive in enabling ongoing and future surveys to tackle the key open problems in cosmology: What is the nature of dark energy? Is it produced by an evolving scalar field? Or does it rather require a modification of the laws of gravity? How does it relate to dark matter? What is the role of neutrinos? The answer to these questions may well revolutionize our view of physics.

1 723 600 €

Start date: 2012-05-01, End date: 2017-10-31

"Logic-based knowledge representation (KR) constitutes a vital area of IT. The field inspires and guides scientific and technological developments enabling intelligent management of large and complex knowledge resources. Elaborate languages for specifying knowledge (so-called ontology languages) and querying it have been defined and standardized. Algorithms for automated reasoning and intelligent querying over knowledge resources are being developed, implemented and practically deployed on a wide scale. Thereby, decidability investigations play a pivotal role to characterize what reasoning or querying tasks are at all computationally solvable. Past decades have seen a proliferation of new decidable formalisms for KR, dominated by two major paradigms: description logics and rule-based approaches, most notably existential rules. Recently, these research lines have started to converge and first progress has been made toward identifying commonalities among the various formalisms. Still, the underlying principles for establishing their decidability remain disparate, ranging from proof-theoretic notions to model-theoretic ones. DeciGUT will accomplish a major breakthrough in the field by establishing a ""Grand Unified Theory"" of decidability. We will provide a novel, powerful model-theoretic criterion inspired by advanced graph-theoretic notions. We will prove that the criterion indeed ensures decidability and that it subsumes most of (if not all) currently known decidable formalisms in the KR field. We will exploit our results toward the definition of novel decidable KR languages of unprecedented expressivity. We will ultimately extend our framework to encompass more advanced KR features beyond standard first order logic such as counting and non-monotonic aspects. Our research will draw from and significantly impact the scientific fields of AI, Database Theory and Logic, but also give rise to drastically improved practical information management technology."

1 814 937 €

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

Deep learning is revolutionizing the field of Natural Language Processing (NLP), with breakthroughs in machine translation, speech recognition, and question answering. New language interfaces (digital assistants, messenger apps, customer service bots) are emerging as the next technologies for seamless, multilingual communication among humans and machines. From a machine learning perspective, many problems in NLP can be characterized as structured prediction: they involve predicting structurally rich and interdependent output variables. In spite of this, current neural NLP systems ignore the structural complexity of human language, relying on simplistic and error-prone greedy search procedures. This leads to serious mistakes in machine translation, such as words being dropped or named entities mistranslated. More broadly, neural networks are missing the key structural mechanisms for solving complex real-world tasks requiring deep reasoning. This project attacks these fundamental problems by bringing together deep learning and structured prediction, with a highly disruptive and cross-disciplinary approach. First, I will endow neural networks with a "planning mechanism" to guide structural search, letting decoders learn the optimal order by which they should operate. This makes a bridge with reinforcement learning and combinatorial optimization. Second, I will develop new ways of automatically inducing latent structure inside the network, making it more expressive, scalable and interpretable. Synergies with probabilistic inference and sparse modeling techniques will be exploited. To complement these two innovations, I will investigate new ways of incorporating weak supervision to reduce the need for labeled data. Three highly challenging applications will serve as testbeds: machine translation, quality estimation, and dependency parsing. To maximize technological impact, a collaboration is planned with a start-up company in the crowd-sourcing translation industry.

1 436 000 €

Start date: 2018-02-01, End date: 2023-01-31

The first direct detection of gravitational waves demonstrated that double black hole (BH) binaries exist, and can host surprisingly massive objects (> 20 solar masses). Most theoretical models do not predict the existence of such massive BHs, and the formation channels of BH binaries are essentially unconstrained. Dynamically formed BH binaries are the most elusive ones: current models either neglect them or study them in idealized systems. With DEMOBLACK, I will draw the first satisfactory picture of BH binary demography, by modeling realistic BH dynamics in a well-motivated cosmological context. I propose a novel approach for the study of BH dynamics: I will simulate the formation of BH binaries in star clusters self-consistently, starting from the hydrodynamics of the parent molecular cloud and accounting for the impact of stellar evolution, feedback, and dynamics on BH binaries. The key tool of DEMOBLACK is SEVN, my new population-synthesis code. With SEVN, I predicted the formation of massive BHs from metal-poor stars, before the first direct detection of gravitational waves. I will interface SEVN with a hydrodynamical code and with an N-body code, to study the formation of BH binaries self-consistently. I will then model the history of BH binaries across cosmic time, accounting for the evolution of metallicity. This novel approach is decisive to break degeneracies between dynamically formed and primordial BH binaries, and to make predictions for future observations by ground-based and space-borne gravitational wave interferometers.

1 994 764 €

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

Deep Learning is one of the most vibrant areas of contemporary machine learning and one of the most promising approaches to Artificial Intelligence. Deep Learning drives the latest systems for image, text, and audio processing, as well as an increasing number of new technologies. The goal of this project is to advance on key open problems in Deep Learning, specifically regarding the capacity, optimization, and regularization of these algorithms. The idea is to consolidate a theoretical basis that allows us to pin down the inner workings of the present success of Deep Learning and make it more widely applicable, in particular in situations with limited data and challenging problems in reinforcement learning. The approach is based on the geometry of neural networks and exploits innovative mathematics, drawing on information geometry and algebraic statistics. This is a quite timely and unique proposal which holds promise to vastly streamline the progress of Deep Learning into new frontiers.

1 500 000 €

Start date: 2018-07-01, End date: 2023-06-30

There are three components to this project: Theory; Empirical Testing; and Dissemination. All components are linked to the current policy question of how taxes influence debt and systemic risk, and all use novel dynamic structural models. I am unique in explicitly linking such models to empirical testing. Theory: “Learning, Capital Structure and Systemic Risk.” Standard dynamic structural models of financing assume firms know the stochastic process governing cash flow. I will first consider a partial equilibrium model. Here firms are exposed to rare event risk, with the true probability being unknown. Firms learn and update beliefs regarding risk. Relative to standard models, firms are debt conservative and there is leverage persistence. In many cases, firms increase leverage only if they have avoided a negative shock long enough. In order to analyze asset pricing implications, I plan to embed such firms in a general equilibrium setting with a common catastrophic risk having unknown probability. Firms rationally respond to “Great Moderations” by increasing leverage. Recessions are more severe after long tranquil periods due to high debt overhang. A third paper, Re-Examining the Link Between Leverage and Systematic Risk, considers cross sectional asset pricing implications of credit shocks. The standard levered beta formula is erroneous, and the pre-tax cost of capital increases with debt. Together, the models show privately optimal debt is lower than recognized, and that tax breaks for debt reduce welfare. Empirical Testing: “Natural Experiment Policy Evaluation—A Structural Critique.” A common approach to testing whether taxes influence corporate financing and investment decisions is to compare leverage and investment before/after tax changes. I use a structural model as a laboratory to show that lack of a statistically significant change is not sufficient to reject the null that “taxes matter.” I will first consider an economy where the tax rate is a Markov process. Flotation costs on debt and real irreversibility limit the response of financing and investment to changes in shadow prices. More importantly, responses to tax changes are attenuated whenever they are partially anticipated and not permanent. Standard tests violate rational expectations by implicitly assuming tax changes come as surprises, with each new change being viewed as permanent, until the next surprise. My argument implies that standard tax experiments cannot falsify the null that taxes affect behaviour. Further, one cannot generalize elasticities if the policy transition matrix differs. I will propose an alternative Bayesian approach to hypothesis testing. My argument casts doubt on standard interpretations of historical evidence of tax change effects, suggesting true elasticities may be much higher. I will consider extending this argument to settings with endogenous policy choices. “Dissemination. The objective of this phase is to lower entry barriers by making the methodology accessible via a non-technical primer, and by making the models readily available using a user-friendly online platform.

1 103 996 €

Start date: 2011-10-01, End date: 2015-09-30

The computation of equilibria in dynamic stochastic general equilibrium models with heterogeneous agents has become increasingly important in macroeconomics and public finance. For a given example-economy, i.e. a given specification of preferences, technologies and market-arrangements these methods compute an (approximate) equilibrium and allow for quantitative statements about one equilibrium of the example-economy. Through these so-called 'computational experiments' many economic insights can be obtained by analyzing quantitative features of realistically calibrated models. Unfortunately, economists often use ad hoc computational methods with poorly understood properties that produce approximate solutions of unknown quality. The research-project outlined in this proposal has three goals: Building theoretical foundations for analyzing dynamic equilibrium models, developing efficient and stable algorithms for the computation of equilibria in large scale models and applying these algorithms to macroeconomic policy analysis.

1 114 800 €

Start date: 2011-10-01, End date: 2016-09-30

The primary questions that drive the Mars exploration program focus on life. Has the Martian climate ever been favorable for life development? Such scenario would imply a distinct planetary system from today with a magnetic flied able to retain the atmosphere. Where is the evidence of such past climate and intern conditions? The clues for answering these questions are locked up in the geologic record of the planet. The volume of data acquired in the past 15 years by the 4 Martian orbiters (ESA and NASA) reach the petaoctet, what is indecent as regard to the size of the Martian community. e-Mars propose to built a science team composed by the PI, Two post-doctorates, one PhD student and one engineer to exploit the data characterizing the surface of Mars. e-Mars proposes the unprecedented approach to combine topographic data, imagery data in diverse spectral domain and hyperspectral data from multiple orbiter captors to study the evolution of Mars and to propose pertinent landing sites for next missions. e-Mars will focus on three scientific themes: the composition of the Martian crust to constraint the early evolution of the planet, the research of possible habitable places based on evidence of past liquid water activity from both morphological record and hydrated mineral locations, and the study of current climatic and geological processes driven by the CO2 cycle. These scientific themes will be supported by three axis of methodological development: the geodatabase management via Geographic Information Systems (G.I.S.)., the automatic hyperspectral data analysis and the age estimates of planetary surface based on small size crater counts.

1 392 000 €

Start date: 2011-11-01, End date: 2017-10-31

A growing number of scholars are studying the interactions between cultural values, social and religious norms, institutions, and economic outcomes. The rise of markets, as well as the development of contracts that enable mutually beneficial transactions among agents, are one of the central themes in the literature on long-term economic growth. This project contributes to both strands of literature by studying the invention and development of marine insurance contracts in medieval Italy and their subsequent spread all over Europe. It brings the economic approach to previously unexplored historical data housed in archives in Florence, Genoa, Pisa, Palermo, Prato, and Venice. The interest in the historical origin and development of marine insurance contracts is twofold. First, marine contracts are the “parents” of all the other insurance contracts (e.g., fire, life, health, etc) that were developed in subsequent centuries to cope with risk. Second, their invention, as well as other innovations in business practices in the Middle Ages, contributed to the growth of international trade in subsequent centuries. The key novelty of the project stems from combining contract theory with information from thousands of insurance contracts between 1300 and 1550 to explain why marine insurance developed in medieval Italy and then Europe, to study the empirical determinants of insurance contracts in medieval Italy, and to analyze how medieval merchants coped with adverse selection and moral hazard problems. Most scholars agree that marine insurance was unknown to the ancient world. Italian merchants developed the first insurance contracts and other innovations in business practices during and in the aftermath of the Commercial Revolution that swept Europe from roughly 1275 to about 1325. Marine insurance contracts may have developed as a spin-off of earlier contracts which shifted the risk from one party to another (e.g., sea loan, insurance loan). Alternatively, in the early or mid-fourteenth century, sedentary merchants that provided the capital to travelling merchants invented a new type of contract, when they discovered that the existing contract forms had shortcomings in transferring and dividing sea risk. A sample of the questions that this project will address includes: - Why did insurance contracts and a marine insurance market first develop in medieval times and not earlier despite merchants had to deal with the risks associated with maritime trade since antiquity? - What were the empirical determinants of contract form (e.g., insurance premium) in the medieval insurance market? - How did medieval merchants compute insurance premia without having the formal notion of probability that was developed only in the mid-seventeenth century? - How did medieval merchants cope with the typical problems that plague insurance markets, i.e., adverse selection and moral hazard?

1 113 900 €

Start date: 2012-07-01, End date: 2018-06-30

The goal of this project is to discover the first galaxies that formed after the Big Bang. The astrophysics of galaxy formation is deeply fascinating. From tiny density fluctuations of quantum mechanical nature believed to have formed during an inflationary period a tiny fraction of a second after the Big Bang during structure slowly formed through gravitational collapse. This process is strongly dependent on the nature of the dominant, but unknown form of matter - the dark matter. In the project proposed here I will study the epoch of first galaxy formation and the subsequent few billion years of cosmic evolution using gamma-ray bursts and Lyman-α (Lyα) emitting galaxies as probes. I am the principal investigator on two observational projects utilizing these probes. In the first project, I will over three years starting October 2009 be using the new X-shooter spectrograph on the European Southern Observatory Very Large Telescope to build a sample of ~100 gamma-ray bursts with UV/optical/near-IR spectroscopic follow-up. The objective of this project is to measure primarily metallicities, molecular content, and dust content of the gamma-ray burst host galaxies. I am primarily interested in the redshift range from 9 to 2 corresponding to about 500 million years to 3 billions years after the Big Bang. In the 2nd project we will use the new European Southern Observatory survey telescope VISTA. I am co-PI of the Ultra-VISTA project that over the next 5 years starting December 2009 will create an ultradeep image (about 2000 hr of total integration time) of a piece of sky known as the COSMOS field. I am responsible for the part of the project that will use a narrow-band filter to search for Lyα emitting galaxies at a redshift of 8.8 (corresponding to about 500 million years after the Big Bang) - believed to correspond to the epoch of formation of some of the very first galaxies.

1 002 000 €

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

Computer systems have become critical to modern society, but they are pervasively subject to security flaws and malicious attacks, with large-scale exposures of confidential data, denial-of-service and ransom attacks, and the threat of nation-state attackers: they are trusted, but are far from trustworthy. This is especially important for the major pan-industry components of our information infrastructure: processors, programming languages, operating systems, etc. The basic problem is that conventional engineering techniques suffice only to make systems that *usually* work. The usual test-and-debug development methods, with poorly specified abstractions described in prose, lack the mathematical rigour of other engineering disciplines - yet the huge investment in legacy systems and skills makes it hard to improve. ELVER will develop *mathematically rigorous* methods for specifying, testing, and reasoning about *real systems*, focussed on the core mechanisms used by hardware and software to enforce security boundaries. It will establish mathematical models for the industry ARM architecture, used pervasively in mobile phones and embedded devices, and the CHERI research architecture, which protects against many attacks. Using these, ELVER will build tools for analysis of system software, develop techniques for mathematical proof of safety and security properties, and explore improved systems programming languages. ELVER will build on successful collaborations with ARM, IBM, and the C/C++ ISO standards committees. It will directly impact mainstream processor architectures, languages, and development methods, smoothly complementing existing methods while simultaneously enabling longer-term research towards the gold standard of provably secure systems. ELVER will thus demonstrate the feasibility and benefits of a more rigorous approach to system engineering, putting future systems on more solid foundations, and hence making them safer and more secure

2 473 844 €

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

This proposal presents three broad projects on information frictions in households' credit markets and on the consequences of these frictions for durable good markets. Specifically, an influential theoretical literature in information economics has shown that borrowing constraints can arise in equilibrium when borrowers and lenders have asymmetric information about borrowers' risks. Hence, the first project aims to provide the first empirical analyses of markets (i.e., demand and supply) with asymmetric information and nonexclusive trades---i.e., markets in which households can purchase multiple insurance contracts, such as in life insurance markets, or can open multiple credit lines, such as in credit card markets. The second project aims to study recent regulations of fees and prices in markets for consumer financial products, such as mortgages, that could have the unintended consequences of increasing households' cost of credit and, thus, of tightening their borrowing constraints. Finally, the third project aims to study the role of borrowing constraints in durable goods markets, with a special focus on car markets during the Great Recession. All these projects aim to develop and estimate structural models using data from different markets. I further plan to use the estimated structural parameters to perform counterfactual policy analyses in each of the specific markets analyzed in these projects.

1 550 945 €

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

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

"My proposal deals with the estimation of Dynamic Stochastic General Equilibrium models with important heterogeneity at the level of firms and households and frictions in the labor market. In the estimation I will exploit mixed frequency data (monthly, quarterly and annual) available in different countries. I will also efficiently take care of possible missing values in the data. This might require developing new estimation techniques. The contribution of the project will be in dealing with important empirically relevant questions. I will address issues that lie at the boundaries between labour economics, business cycle analysis, monetary economics, finance, and growth. In particular I will answer the following questions: 1. How are business cycle costs distributed across different individuals? How costly is involuntary unemployment? 2. Which view best characterizes the process of technology adoption at business cycle frequencies? In particular does Schumpeterian creative destruction play a role in characterizing the adoption of new technologies over the business cycle? 3. What are the welfare costs of the search inefficiencies present in the process of worker reallocation over the business cycle? 4. What are the sources of business cycle fluctuations? And in particular are technology shocks an important driving force? 5. What are the contribution of the job separation rate and the importance of the intensive margin relative to the extensive margin in characterizing aggregate labor market fluctuations? 6. What are the main differences in the cyclical properties of the labor market across the OECD? And which institutions explain these differences? 7. What are the effects of financial sector shocks? And why has the Beveridge curve shifted during the last world wide recession? 8. How policy should respond to the large variation in unemployment risk that individual workers face over their life cycle?"

1 659 169 €

Start date: 2012-03-01, End date: 2017-02-28

Economics provides decision-makers with powerful tools to analyse a wide range of issues. The methodological unity of the discipline and its quest for a general understanding of market as well as non-market interactions have given the discipline great influence on policy. A core component of economics is its assumption that individuals act as if they each had some goal function that they seek to maximise, under the constraints they face and the information they have. Despite significant advances in behavioural economics, there still is no consensus as to whether and why certain preferences are more likely than others. Further progress could be made if the factors that shape human motivation in the first place were understood. The aim of this project is to produce novel insights about such factors, by establishing evolutionary foundations of human motivation.The project's scope is ambitious. First, it will study two large classes of interactions: strategic interactions, and interactions within the realm of the family. Second, to obtain both depth and breadth of insights, it will consist of four different, but inter-related, components (three theoretical and one empirical), the ultimate goal being to significantly enhance our overall understanding of the factors that shape human motivation. The methodology is ground-breaking in that it is strongly interdisciplinary. Parts of the body of knowledge built by biologists and evolutionary anthropologists in the past decades will be combined with state-of-the-art economics to produce insights that cannot be obtained within any single discipline. Focus will nonetheless be on addressing issues of importance for economists.The proposed research builds on extensive work done by the PI in the past decade. It will benefit from the years that the PI has invested in understanding the biology and the evolutionary anthropology literatures, and in contributing towards building an interdisciplinary research ecosystem in Toulouse, France

1 550 891 €

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

The detection of life beyond our Solar System is possible only via the remote sensing of the atmospheres of exoplanets. The recent discovery that small exoplanets are common around cool, red stars offers an exciting opportunity to study the atmospheres of Earth-like worlds. Motivated by this revelation, the EXOKLEIN project proposes to construct a holistic climate framework to understand astronomical observations in the context of the atmosphere, geochemistry and biosignatures of the exoplanet. The proposed research is divided into three major themes. Research Theme 1 aims to construct a virtual laboratory of an atmosphere that considers atmospheric dynamics, chemistry and radiation, as well as how they interact. This virtual laboratory enables us to understand the physical and chemical mechanisms involved, as well as predict the observed properties of an exoplanet. Research Theme 2 aims to generalize the carbonate-silicate cycle (also known as the long-term carbon cycle) by considering variations in rock composition, water acidity and atmospheric conditions. The carbonate-silicate cycle is important because it regulates the long-term presence of carbon dioxide (a vital greenhouse gas) in atmospheres. We also aim to investigate the role of the cycle in determining the fates of ocean-dominated exoplanets called “water worlds”. Research Theme 3 aims to investigate the long-term stability of biosignature gases in the context of the climate. Whether a gas uniquely indicates the presence of biology on an exoplanet depends on the atmospheric properties and ultraviolet radiation environment. We investigate three prime candidates for biosignature gases: methyl chloride, dimethylsulfide and ammonia. Overall, the EXOKLEIN project will significantly advance our understanding of whether the environments of rocky exoplanets around red stars are stable and conducive for life, and whether the tell-tale signatures of life may be detected by astronomers.

1 984 729 €

Start date: 2018-02-01, End date: 2023-01-31

We propose to lay the theoretical foundations and design efficient computational methods for analyzing, quantifying and exploring relations and variability in structured data sets, such as collections of geometric shapes, point clouds, and large networks or graphs, among others. Unlike existing methods that are tied and often limited to the underlying data representation, our goal is to design a unified framework in which variability can be processed in a way that is largely agnostic to the underlying data type. In particular, we propose to depart from the standard representations of objects as collections of primitives, such as points or triangles, and instead to treat them as functional spaces that can be easily manipulated and analyzed. Since real-valued functions can be defined on a wide variety of data representations and as they enjoy a rich algebraic structure, such an approach can provide a completely novel unified framework for representing and processing different types of data. Key to our study will be the exploration of relations and variability between objects, which can be expressed as operators acting on functions and thus treated and analyzed as objects in their own right using the vast number of tools from functional analysis in theory and numerical linear algebra in practice. Such a unified computational framework of variability will enable entirely novel applications including accurate shape matching, efficiently tracking and highlighting most relevant changes in evolving systems, such as dynamic graphs, and analysis of shape collections. Thus, it will permit not only to compare or cluster objects, but also to reveal where and how they are different and what makes instances unique, which can be especially useful in medical imaging applications. Ultimately, we expect our study to create to a new rigorous, unified paradigm for computational variability, providing a common language and sets of tools applicable across diverse underlying domains.

1 499 845 €

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

Social computing represents a societal-scale symbiosis of humans and computational systems, where humans interact via and with computers, actively providing inputs to influence and being influenced by, the outputs of the computations. Recently, several concerns have been raised about the unfairness of social computations pervading our lives ranging from the potential for discrimination in machine learning based predictive analytics and implicit biases in online search and recommendations to their general lack of transparency on what sensitive data about users they use or how they use them. In this proposal, I propose ten fairness principles for social computations. They span across all three main categories of organizational justice, including distributive (fairness of the outcomes or ends of computations), procedural (fairness of the process or means of computations), and informational fairness (transparency of the outcomes and process of computations) and they cover a variety of unfairness perceptions about social computations. I describe the fundamental and novel technical challenges that arise when applying these principles to social computations. These challenges are related to operationalization (measurement), synthesis and analysis of fairness in computations. Tackling these requires applying methodologies from a number of sub-areas within CS, including learning, datamining, IR, game-theory, privacy, and distributed systems. I discuss our recent breakthroughs in tackling some of these challenges, particularly our idea of fairness constraints, a flexible mechanism that allows us to constrain learning models to synthesize fair computations that are non-discriminatory, the first of our ten principles. I outline our plans to build upon our results to tackle the challenges that arise from the other nine fairness principles. Successful execution of the proposal will provide the foundations for fair social computing in the future.

2 487 500 €

Start date: 2018-07-01, End date: 2023-06-30

Preferences are a representation of individuals’ behavioral goals. Assumptions about individual preferences are a decisive component of almost all economic models. In fact, any social science that aims at explaining both individual behaviors and aggregate outcomes in terms of individuals’ goals and constraints has to make assumptions about preferences. Knowledge about preferences is thus key for the ability to predict the behavior of individuals and groups, and for assessing the welfare consequences of different policies. There are, however, still large empirical gaps in our knowledge about preferences. Extremely little is known about the social, economic and biological factors that causally shape them. There is also limited knowledge about how preferences are distributed in society, how they relate to demographic and socio-economic factors, how time, risk and social preferences are interrelated, and the extent to which preferences are stable across time and strategic situations. Therefore, we propose to study these foundational questions by applying economic and neuroeconomic tools that enable us to measure structural preference parameters and the social and biological forces that shape them. In particular, we will study the four following topics. (1) The distribution and stability of time, risk and social preference parameters based on nationally representative behavioral experiments. (2) The relationship between time, risk and social preferences. (3) The causal impact of the social environment on preferences. (4) The neural and genetic determinants of preferences. The proposed research program promises to yield important insights into the causal determinants, the structure and the relationships between time, risk and social preferences. This will inform and constrain theoretical models and policy conclusions based on such models.

2 494 759 €

Start date: 2012-08-01, End date: 2018-07-31

How does financial market development affect employment, wages and unemployment risk? And how do labor market institutions and workers’ behavior in turn affect corporate policies? These issues are much under-researched, in spite of their prominence in public debate, often ideologically polarized between those who consider finance as socially harmful and those who view it as an efficient allocation machine. Most economic research indicates that financial development raises output growth, but is silent about its effects on the labor market: does it also raise employment and wages? If so, is it at the expense of greater employment risk and inequality? And how does the potential for systemic financial instability affect the answers to these questions? The study of these issues naturally opens also another – equally under-researched – line of inquiry: that concerning the effects of labor relations on financial arrangements. Do corporate investment policies and leverage decisions take into account their own effects on firms’ bargaining position in wage negotiations? And if so, how are these corporate decisions affected by job protection regulation, union density or workers’ protection in bankruptcy? To what extent do companies insure workers against employment risk, and do family and non-family firms differ in this respect? Finally, can labor market competition damage the performance of employees with decision-making responsibilities? For instance, can it induce managers or traders to take excessively risky decisions, by providing them with an escape route once they make mistakes, especially when outcomes are observed long after decisions? This research project purports to break new ground on both sets of issues, using a combination of analytical modelling and empirical analysis, which in some cases will require the collection of entirely new data.

1 873 800 €

Start date: 2012-07-01, End date: 2018-06-30

A vision for the future are autonomous and semi-autonomous systems that perform complex tasks safely and robustly in interaction with humans and the environment. The action of such a system needs to be carefully planned and executed, taking into account the available sensory feedback and knowledge about the environment. Many of the existing approaches view motion planning as a geometrical problem, not taking the uncertainty into account. Our goal is to study how different type of representations and algorithms from the area of machine learning and classical mathematics can be used to solve some of the open problems in the area of action recognition and action generation. FLEXBOT will explore how how topological representations can be used for an integrated approach toward i) vision based understanding of complex human hand motion, ii) mapping and control of robotics hands and iii) integrating the topological representations with models for high-level task encoding and planning. Our research opens for new and important areas scientifically and technologically. Scientifically, we push for new way of thinking in an area that has traditionally been born from mechanical modeling of bodies. Technologically, we will provide methods plausible for evaluation of new designs of robotic and prosthetic hands. Further development of machine learning and computer vision methods will allow for scene understanding that goes beyond the assumption of worlds of rigid bodies, including complex objects such as hands.

1 398 720 €

Start date: 2012-01-01, End date: 2017-12-31

"Natural language understanding is the ""holy grail"" of computational linguistics and a long-term goal in research on artificial intelligence. Understanding human communication is difficult due to the various ambiguities in natural languages and the wide range of contextual dependencies required to resolve them. Discovering the semantics behind language input is necessary for proper interpretation in interactive tools, which requires an abstraction from language-specific forms to language-independent meaning representations. With this project, I propose a line of research that will focus on the development of novel data-driven models that can learn such meaning representations from indirect supervision provided by human translations covering a substantial proportion of the linguistic diversity in the world. A guiding principle is cross-lingual grounding, the effect of resolving ambiguities through translation. The beauty of that idea is the use of naturally occurring data instead of artificially created resources and costly manual annotations. The framework is based on deep learning and neural machine translation and my hypothesis is that training on increasing amounts of linguistically diverse data improves the abstractions found by the model. Eventually, this will lead to universal sentence-level meaning representations and we will test our ideas with multilingual machine translation and tasks that require semantic reasoning and inference."

1 817 622 €

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

The use of Computer Graphics (CG) is constantly expanding, e.g., in Virtual and Augmented Reality, requiring realistic interactive renderings of complex virtual environments at a much wider scale than available today. CG has many limitations we must overcome to satisfy these demands. High-quality accurate rendering needs expensive simulation, while fast approximate rendering algorithms have no guarantee on accuracy; both need manually-designed expensive-to-create content. Capture (e.g., reconstruction from photos) can provide content, but it is uncertain (i.e., inaccurate and incomplete). Image-based rendering (IBR) can display such content, but lacks flexibility to modify the scene. These different rendering algorithms have incompatible but complementary tradeoffs in quality, speed and flexibility; they cannot currently be used together, and only IBR can directly use captured content. To address these problems FunGraph will revisit the foundations of Computer Graphics, so these disparate methods can be used together, introducing the treatment of uncertainty to achieve this goal. FunGraph introduces estimation of rendering uncertainty, quantifying the expected error of rendering components, and propagation of input uncertainty of captured content to the renderer. The ultimate goal is to define a unified renderer exploiting the advantages of each approach in a single algorithm. Our methodology builds on the use of extensive synthetic (and captured) “ground truth” data, the domain of Uncertainty Quantification adapted to our problems and recent advances in machine learning – Bayesian Deep Learning in particular. FunGraph will fundamentally transform computer graphics, and rendering in particular, by proposing a principled methodology based on uncertainty to develop a new generation of algorithms that fully exploit the spectacular (but previously incompatible) advances in rendering, and fully benefit from the wealth offered by constantly improving captured content.

2 497 161 €

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

The GEODESI project aims at interpreting current and forthcoming cosmological observations in a renewed theoretical framework about cosmological inflation and its ending. The simplest toy models of inflation economically explain all current data, leaving no observational clue to guide theorists towards a finer physical understanding. In this context, I very recently unveiled an hitherto unnoticed instability at play in the primordial universe that potentially affects all inflationary models and drastically modifies the interpretation of cosmological observations in terms of fundamental physics. The so-called Geometrical Destabilization of inflation reshuffles our understanding of the origin of structures in the universe, offers a new mechanism to end inflation, and promises unrivaled constraints on high-energy physics. It is crucial to develop this fresh look before a host of high-quality data from large-scale structure surveys and cosmic microwave background observations become available within the 5 year timescale of the project. With the ERC grant I plan to build a group at the Institute of Astrophysics of Paris (IAP-CNRS) with the objective of determining the full theoretical and observational consequences of the geometrical destabilization of inflation. We will combine insights from non-standard cosmological perturbation theory and lattice simulations to constrain realistic models of inflation in high-energy physics, producing accurate theoretical predictions for a wide variety of observables, including the spectra and the non-Gaussianities of primordial fluctuations and stochastic backgrounds of gravitational waves.

1 476 672 €

Start date: 2018-02-01, End date: 2023-01-31

"This proposal is divided into two main strands. The first strand seeks to understand the effects of local marginal institutional change in autocracies. In particular, we will examine the introduction of local democracy in rural China. Our first contribution is to collect a representative panel of villages in rural China. With this unique data we will examine three main questions: First, we will establish the effect of the introduction of local elections on policies that are determined at the village level: land allocation, tax collection, public good provision and the enforcement of the one child policy. Second, the data will provide a unique opportunity to explore the interaction between formal and informal institutions of accountability by leveraging our information on social infrastructure in these villages. Third, we will determine whether leaders' characteristics change with the introduction of elections. These unique data will also set the stage for examining many other recent policy reforms in rural China. The second strand of the proposal seeks to focus the formal conflict literature to the study of insurgencies, a currently prevalent form of organized violence in developing countries. To capture the basic characteristics of these conflicts, we need models that allow for (i) meaningful conflict dynamics, (ii) a central role for the non-combatant population, (iii) fundamental asymmetry between government and insurgents and (iv) economic transfers and service provision as a strategic ability of the contenders. To reach this goal we will build a series of models whose main contribution to the formal literature of conflict is the introduction of tools from the dynamic principal agent framework. Several building blocks will be analyzed before integrating them in a coherent theory of insurgency from which optimal policy and empirical implications can be derived."

805 089 €

Start date: 2012-07-01, End date: 2017-06-30