ERC FUNDED PROJECTS

"Contemporary database query languages are ultimately founded on logic and feature an additive operation – usually a form of (multi)set union or disjunction – that is asymmetric in that additions or updates do not always have an inverse. This asymmetry puts a greater part of the machinery of abstract algebra for equation solving outside the reach of databases. However, such equation solving would be a key functionality that problems such as query equivalence testing and data integration could be reduced to: In the current scenario of the presence of an asymmetric additive operation they are undecidable. Moreover, query languages with a symmetric additive operation (i.e., which has an inverse and is thus based on ring theory) would open up databases for a large range of new scientific and mathematical applications. The goal of the proposed project is to reinvent database management systems with a foundation in abstract algebra and specifically in ring theory. The presence of an additive inverse allows to cleanly define differences between queries. This gives rise to a database analog of differential calculus that leads to radically new incremental and adaptive query evaluation algorithms that substantially outperform the state of the art techniques. These algorithms enable a new class of systems which I call Dynamic Data Management Systems. Such systems can maintain continuously fresh query views at extremely high update rates and have important applications in interactive Large-scale Data Analysis. There is a natural connection between differences and updates, motivating the group theoretic study of updates that will lead to better ways of creating out-of-core data processing algorithms for new storage devices. Basing queries on ring theory leads to a new class of systems, Algebraic Data Management Systems, which herald a convergence of database systems and computer algebra systems."

1 480 548 €

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

Since the invention of the spinning frame, automation has been one of the drivers of economic growth. Yet, workers, economist or the general public have been concerned that automation may destroy jobs or create inequality. This concern is particularly prevalent today with the sustained rise in economic inequality and fast technological progress in IT, robotics or self-driving cars. The empirical literature has showed the impact of automation on income distribution. Yet, the level of wages itself should also affect the incentives to undertake automation innovations. Understanding this feedback is key to assess the long-term effect of policies. My project aims to provide the first quantitative account of the two-way relationship between automation and the income distribution. It is articulated around three parts. First, I will use patent data to study empirically the causal effect of wages on automation innovations. To do so, I will build firm-level variation in the wages of the customers of innovating firms by exploiting variations in firms’ exposure to international markets. Second, I will study empirically the causal effect of automation innovations on wages. There, I will focus on local labour market and use the patent data to build exogenous variations in local knowledge. Third, I will calibrate an endogenous growth model with firm dynamics and automation using Danish firm-level data. The model will replicate stylized facts on the labour share distribution across firms. It will be used to compute the contribution of automation to economic growth or the decline of the labour share. Moreover, as a whole, the project will use two different methods (regression analysis and calibrated model) and two different types of data, to answer questions of crucial policy importance such as: Taking into account the response of automation, what are the long-term effects on wages of an increase in the minimum wage, a reduction in labour costs, or a robot tax?

1 295 890 €

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

The goal of this proposal is to fundamentally change the way we build and reason about software. We aim to develop new kinds of statistical programming systems that provide probabilistically likely solutions to tasks that are difficult or impossible to solve with traditional approaches. These statistical programming systems will be based on probabilistic models of massive codebases (also known as ``Big Code'') built via a combination of advanced programming languages and powerful machine learning and natural language processing techniques. To solve a particular challenge, a statistical programming system will query a probabilistic model, compute the most likely predictions, and present those to the developer. Based on probabilistic models of ``Big Code'', we propose to investigate new statistical techniques in the context of three fundamental research directions: i) statistical program synthesis where we develop techniques that automatically synthesize and predict new programs, ii) statistical prediction of program properties where we develop new techniques that can predict important facts (e.g., types) about programs, and iii) statistical translation of programs where we investigate new techniques for statistical translation of programs (e.g., from one programming language to another, or to a natural language). We believe the research direction outlined in this interdisciplinary proposal opens a new and exciting area of computer science. This area will combine sophisticated statistical learning and advanced programming language techniques for building the next-generation statistical programming systems. We expect the results of this proposal to have an immediate impact upon millions of developers worldwide, triggering a paradigm shift in the way tomorrow's software is built, as well as a long-lasting impact on scientific fields such as machine learning, natural language processing, programming languages and software engineering.

1 500 000 €

Start date: 2016-04-01, End date: 2021-03-31

Systemic sclerosis (SSc) is an autoimmune disease that culminates in excessive extra-cellular matrix deposition (fibrosis) in skin and internal organs. SSc is a severe disease in which fibrotic events lead to organ failure such as renal failure, deterioration of lung function and development of pulmonary arterial hypertension (PAH). Together, these disease hallmarks culminate in profound disability and premature death. Over the past three years several crucial observations by my group changed the landscape of our thinking about the ethiopathogenesis of this disease. First, plasmacytoid dendritic (pDCs) cells were found to be extremely frequent in the circulation of SSc patients (1000-fold) compared with healthy individuals. In addition, we observed that pDCs from SSc patients are largely dedicated to synthesize CXCL4 that was proven to be directly implicated in fibroblast biology and endothelial cell activation, two events recapitulating SSc. Finally, research aimed to decipher the underlying cause of this increased pDCs frequency led to the observation that Runx3, a transcription factor that controls the differentiation of DC subsets, was almost not expressed in pDC of SSc patients. Together, these observations led me to pose the “SSc immune postulate” in which the pathogenesis of SSc is explained by a multi-step process in which Runx3 and CXCL4 play a central role. The project CIRCUMVENT is designed to provide proof of concept for the role of CXCL4 and RUNX3 in SSc. For this aim we will exploit a unique set of patient material (cell subsets, protein and DNA bank), various recently developed in vitro techniques (siRNA for pDCs, viral over expression of CXCL4/RUNX3) and apply three recently optimised experimental models (CXCL4 subcutaneous pump model, DC specific RUNX3 KO and the SCID/NOD/rag2 KO mice). The project CIRCUMVENT aims to proof the direct role for Runx3 and CXCL4 that could provide the final step towards the development of novel therapeutic targets

1 500 000 €

Start date: 2012-08-01, End date: 2017-07-31

This proposal aims to provide insight into how bacteria are killed by the complement system, an important part of the host immune response against bacterial infections. Complement is a large protein network in plasma that labels bacteria for phagocytosis and directly kills them via the formation of a pore-forming complex (Membrane Attack Complex (MAC)). Currently we do not understand how complement activation results in bacterial killing. This knowledge gap is mainly caused by the lack of tools to study the enzymes that trigger MAC formation: the C5 convertases. In my lab, we recently established a novel assay system for C5 convertases that allows us for the first time to study these enzymes under purified conditions. This model, combined with my expertise in microbiology, places my lab in a unique position to understand C5 convertase biology (Aim 1), determine the enzyme's role in MAC functioning (Aim 2) and elucidate how the MAC kills bacteria (Aim 3). Thus, I aim to provide insight into the molecular events necessary for bacterial killing by the complement system. I will use biochemical, structural and microbiological approaches to elucidate the precise molecular arrangement of C5 convertases in vitro and on bacterial cells. I will generate unique tools to study how C5 convertases regulate MAC insertion into bacterial membranes. Finally, I will engineer fluorescent bacteria and labeled complement proteins to perform advanced microscopy analyses of how MAC kills bacteria. These insights will lead to fundamental knowledge about the functioning of complement and will create new avenues for blocking the undesired complement activation during systemic infections and acute inflammatory processes. Furthermore this knowledge will improve desired complement activation by therapeutic antibodies and vaccination strategies in infectious diseases. Finally, this work opens up new possibilities to understand how both humans and bacteria regulate complement.

1 497 290 €

Start date: 2015-03-01, End date: 2020-02-29

Power relations are an integral part of economic organizations, as well as political and social institutions. People exercise power over others – or are exposed to the power of others – in government, in firms, and even in families. People care deeply about power and autonomy, and attitudes towards them have important economic and societal consequences. Examples include such diverse matters as the willingness to delegate power to government, empire building in public organizations, or sorting into more or less autonomous jobs. Despite their importance, we have remarkably little knowledge about preferences for power and autonomy. Clearly, power and autonomy are valued for being instrumental in achieving desirable outcomes, but it has also long been argued that they are valuable for their own sake. Existing value measures of power and autonomy, however, fail to distinguish between intrinsic and instrumental value components. Power distance and autonomy are even considered to be cultural values, but we don’t know whether differences in such measures are rooted in differences in the instrumental value or differences in preferences. We propose a novel revealed preference approach that allows us to address this shortcoming by separately measuring the intrinsic value of power and the intrinsic value of autonomy. We can then apply this method to properly assess heterogeneity in such values within and across cultures. By combining our measures with other data, we will be able to study the importance of such preferences in explaining individual differences, such as occupational choices or expressed political views, as well as economic outcomes across countries, such as the level of decentralization in economic organizations. Finally, we will study how behavioral reactions to power interact with such preferences and organizational structure, in order to better understand how institutions can be efficiently designed when behavioral reactions to power are accounted for.

1 492 785 €

Start date: 2019-03-01, End date: 2024-02-29

Cytotoxic T lymphocytes (CTL) and natural killer (NK) cells release granzyme and perforin from cytotoxic granules into the immune synapse to induce apoptosis of target cells that are either virus-infected or cancerous. Granzyme A activates a caspase-independent apoptotic pathway and induces mitochondrial damage characterized by superoxide anion production and loss of the mitochondrial transmembrane potential, without disrupting the integrity of the mitochondrial outer membrane; while causing single-stranded DNA damage. GzmB induces both caspase-dependent and caspase-independent cell death. In the caspase-dependent pathway, mitochondrial functions are altered as evidenced by the loss of mitochondrial transmembrane potential and the generation of reactive oxygen species (ROS). The mitochondrial outer membrane (MOM) is disrupted, resulting in the release of apoptogenic factors. To date, research on mitochondrial-dependent apoptosis has focused on mitochondrial outer membrane permeabilization (MOMP) however whether the generation of ROS is incidental or essential to the execution of apoptosis remains unclear. Like human GzmA, human GzmB promotes cell death in a ROS-dependent manner. Preliminary data suggest that human GzmB can induce ROS in a MOMP-independent manner as Bax and Bak double knockout MEF cells treated with human GzmB and perforin still display a robust ROS production and dye in an ROS-dependent manner. Since GzmA and GzmB induce cell death in a ROS-dependent manner, we hypothesize that oxygen free radicals are central to the execution of programmed cell death induced by the cytotoxic granules. Therefore, the goal of this proposal is to dissect the key molecular events triggered by ROS that lead to Citotoxic Tcell-induced target cell death. A combination of biochemical, genetic and proteomic approaches in association with Electron Spin Resonance (ESR) spectroscopy methodology will be used to unravel the essential role ROS play in CTL-mediated killing.

1 500 000 €

Start date: 2011-05-01, End date: 2016-04-30

Tax evasion leads to billions of Euros of losses in government revenue around the world. This does not only affect public budgets, but can also create large distortions between activities that are fully taxed and others that escape taxation through evasion. These issues are particularly severe in developing countries, where evasion is especially high and governments struggle to raise funds for basic services and infrastructure, while at the same time trying to grow independent of international aid. It is widely suspected that some of the most common and difficult to detect forms of evasion involve interactions across firm networks. However, due to severe data limitations, the existing literature has mostly considered taxpayers as isolated units. Empirical evidence on tax compliance in firm networks is extremely sparse. This proposal describes 3 Sub-Projects to fill this gap. They are made possible thanks to access I have obtained -through five years of prior research and policy engagement– to unique datasets from Chile and Ecuador on both the networks of supply chains and of joint ownership structures. The first Sub-Project focuses on international firm networks. It aims to analyze profit shifting of multinational firms to low tax jurisdictions, exploiting a natural experiment in Chile that strongly increased monitoring of international tax norms. The second Sub-Project investigates the analogous issue at the intranational level: profit shifting and tax collusion in networks of firms within the same country. Despite much anecdotal evidence, this behavior has received little rigorous empirical scrutiny. The final Sub-Project is situated at the nexus between international and national firms. It seeks to estimate a novel form of spillovers of FDI: the impact on tax compliance of local trading partners of foreign-owned firms. DEVTAXNET will provide new insights about the role of firm networks for tax evasion that are valuable to academics and policy makers alike.

1 288 125 €

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

"Our digital society critically relies on protection of data and communication against espionage and cyber crime. Underlying all protection mechanisms is cryptography, which we are using daily to protect, for example, internet communication or e-banking. This protection is threatened by the dawn of universal quantum computers, which will break large parts of the cryptography in use today. Transitioning current cryptographic algorithms to crypto that resist attacks by large quantum computers, so called ""post-quantum cryptography"", is possibly the largest challenge applied cryptography is facing since becoming a domain of public research in the second half of the last century. Large standardization bodies, most prominently ETSI and NIST, have started efforts to evaluate concrete proposals of post-quantum crypto for standardization and deployment. NIST's effort follows in the tradition of successful public ""crypto competitions"" with strong involvement by the academic cryptographic community. It is expected to run through the next 5 years. This project will tackle the engineering challenges of post-quantum cryptography following two main research directions. The first direction investigates implementation characteristics of submissions to NIST for standardization. These include speed on various platforms, code size, and RAM usage. Furthermore we will study so-called side-channel attacks and propose suitable countermeasures. Side-channel attacks use information such as timing or power consumption of cryptographic devices to obtain secret information. The second direction is about protocol integration. We will examine how different real-world cryptographic protocols can accommodate the drastically different performance characteristics of post-quantum cryptography, explore what algorithms suit best the requirements of common usage scenarios of these protocols, and investigate if changes to the high-level protocol layer are advisable to improve overall system performance."

1 500 000 €

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