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  • OA Publications Mandate: Yes
  • 2019
  • 2024

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  • Funder: WT Project Code: 212246
    Funder Contribution: 990,352 GBP

    Membrane proteins destined for lysosomal degradation are ubiquitinated within the endosome and then sorted into intralumenal vesicles (ILVs), to form the multivesicular body (MVB). This critically important process is exemplified by the sorting of EGF receptor (EGFR). MVB sorting requires ESCRTs (Endosomal Sorting Complexes Required for Transport). ESCRTs collectively recognise ubiquitinated EGFR on the cytoplasmic face of the endosome and capture it within ILVs, whilst they escape. Towards understanding how ESCRTs overcome this topological problem, we will reconstitute the process. We have identified all those ESCRTs that drive EGFR sorting, and how they bind each other. We will now reconstitute MVB sorting, using proteoliposomes containing EGFR and exploiting our full complement of baculovirus-expressed ESCRTs. We will use site-directed photo-crosslinking to map the entire process biochemically, and will complement this with further in vitro analysis of the molecular architecture within the developing ILV. Key conclusions will be verified in cells. Current ideas suggest ubiquitination is the determining factor for EGFR sorting. However, we believe instead that EGFR signalling-dependent activation of ESCRTs is decisive. We will systematically identify ESCRT post-translational modifications (PTMs) that map with MVB sorting, and test using both reconstituted proteoliposomes and in cells how these PTMs control the pathway. Plasma membrane proteins destined for degradation are internalised, enter the endosome, and then transit to the lysosome. Many crucial proteins follow this pathway, with epidermal growth factor receptor (EGFR) an exemplar because of its biological and biomedical importance. EGFR transport to the lysosome requires a crucial event; the receptor is ubiquitinated and then enters membrane vesicles that bud into the lumen of the endosome, to form the multivesicular body. The molecular machinery that drives multivesicular body formation must overcome a complex topological problem: it recognises ubiquitinated EGFR on the cytoplasmic face of the endosome, generates vesicles that capture EGFR inside the endosome, but escapes itself. How this works remains mysterious, but we aim to solve it. We will reassemble the machinery from its component parts on artificial endosomes, and dissect biochemically how it envelops EGFR. We will also examine how the machinery is activated by EGFR, ensuring EGFR’s efficient capture.

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  • Funder: EC Project Code: 818858
    Overall Budget: 2,000,000 EURFunder Contribution: 2,000,000 EUR

    For many years, lymphatic vessels have been viewed as inert fluid conduits whose open structure allows for passive flow of antigens, proteins and cells from peripheral tissues to lymphoid organs. Yet, recent discoveries highlighting novel functions and heterogeneous origins of the lymphatic endothelium, call for reevaluation of the passive lymphatic-vessel paradigm. During the past decade, we have used the zebrafish (ZF) to detail the cellular and molecular events underlying the development of the lymphatic system. Our discoveries have greatly contributed to our understanding of the origins, specification and mechanisms of formation of lymphatic endothelial cells (LECs) in the developing embryo. In line with our past achievements, we now aim towards novel directions- to transform the adult ZF into an equally convenient model for the study of lymphatic diversity. The overall goal of LymphMap is to reveal the multiple regulatory levels that coordinate the formation and functionality of lymphatic vessels in health and disease. To this end, we will carry out a comprehensive research program characterizing four distinct aspects of lymphatic biology: 1.Cellular origins and molecular signature of LECs 2.Formation and specialization of organotypic lymphatics 3.Lymphatic vessels during organ regeneration 4.Lymphatic involvement in human disease Our experimental strategy involves the combination of high-resolution imaging, global expression profiling and regeneration models in adult ZF, with analyses of human-derived LECs in various clinical settings. The important and unique aspects of our approach are the focus on in vivo dynamics, and the cross-organ comparative analysis, which will likely provide the much-needed knowledge on lymphatic diversity in health and disease. When completed, we anticipate that this work will be part of a new paradigm – no longer perceiving lymphatics as passive bystanders, but rather as orchestrators of tissue morphogenesis and regeneration.

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  • Funder: EC Project Code: 833801
    Overall Budget: 2,164,240 EURFunder Contribution: 2,164,240 EUR

    Quantum simulators (QS) are experimental systems that allow mimic hard to simulate models of condensed matter, high energy physics and beyond. QS have various platforms: from ultracold atoms and ions to superconducting qubits. They constitute the important pillar of quantum technologies (QT), and promise future applications in chemistry, material science and optimization problems. Over the last decade, QS were particularly successful in mimicking topological effects in physics (TEP) and in developing accurate quantum validation/certification (QVC) methods. NOQIA is a theory project, aimed at introducing the established field of QS+TEP+QVC into two novel areas: physics of ultrafast phenomena and attoscience (AS) on one side, and quantum machine learning (ML) and neural networks (NN) on the other. This will open up new horizons/opportunities for research both in AS and in ML/NN. For instance, in AS we will address the question if intense laser physics may serve as a tool to detect topological effects in solid state and strongly correlated systems. We will study response of matter to laser pulses carrying topological signatures, to determine if they can induce topological effects in targets. We will design/analyze QS using trapped atoms to understand and detect TEP in the AS. On the ML/NN side, we will apply classical ML to analyze, design and control QS for topological systems, in order to understand and optimize them. Conversely, we will transfer many-body techniques to ML in order to analyze and possibly improve performance of classical machine learning. We will design and analyze quantum neural network devices that will employ topology in order to achieve robust quantum memory or information processing. We will design/study attractor neural networks with topological stationary states, or feed-forward networks with topological Floquet and time-crystal states. Both in AS and ML/NN, NOQIA will rely on quantum validation and certification protocols and techniques.

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  • Funder: EC Project Code: 788851
    Overall Budget: 2,498,530 EURFunder Contribution: 2,498,530 EUR

    NEMO, NEtwork MOtion, is an inter-disciplinary proposal centered on network dynamics. The inter-disciplinarity spans from communication engineering to mathematics, with an innovative interplay between the two. NEMO’s focus is on stochastic geometry. This emerges as one of the most important new conceptual and operational tools of the last 10 years in wireless networking, with a major academic and industrial impact on architecture, protocol design, planning and economic analysis. Nevertheless, the state of the art is unable to cope with the dynamics introduced in recent and future network functionalities. NEMO’s aim is to introduce dynamics in wireless stochastic geometry. The dynamic versions of stochastic geometry to be developed will capture these new functionalities and specifically tackle two core promises and challenges of the future of wireless networking: that of ultra-low latency networking, required for enabling the unfolding of future real time interactions, and that of draining to the Internet the unprecedented amount and structure of data stemming from the Internet of Things. Several fundamental types of random network dynamics underpinning these functionalities are identified. General mathematical tools combining stochastic geometry, random graph theory, and the theory of dynamical systems will be developed to analyze them. This will provide parametric models mastering the complexity of such networks, which will be instrumental in addressing the above challenges. The aim is to have, through these dynamical versions, the same academic and industrial impact on wireless networks as static stochastic geometry has today. NEMO will leverage structural interactions of INRIA with Ecole Normale Supérieure on the mathematical side, and with Nokia Bell Labs and Orange on the engineering side. This will create in Europe a group focused on this mathematics-communication engineering interface, and to become the top innovation group of the field worldwide.

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  • Funder: EC Project Code: 817629
    Overall Budget: 1,999,080 EURFunder Contribution: 1,999,080 EUR

    Engineers and computer scientists are currently developing autonomous systems whose entire set of behaviors in future, untested situations is unknown: How can a designer foresee all situations that an autonomous road vehicle, a robot in a human environment, an agricultural robot, or an unmanned aerial vehicle will face? Keeping in mind that all these examples are safety-critical, it is irresponsible to deploy such systems without testing all possible situations---this, however, seems impossible since even the most important possible situations are unmanageably many. I propose a paradigm shift that will make it possible to guarantee safety in unforeseeable situations: Instead of verifying the correctness of a system before deployment, I propose just-in-time verification, a new, to-be-developed verification paradigm where a system continuously checks the correctness of its next action by itself in its current environment (and only in it) in a just-in-time manner. Since future autonomous systems will have a tight interconnection of discrete computing and continuous physical elements, also known as cyber-physical systems, I will develop just-in-time verification for this system class. In order to prove correct behavior of cyber-physical systems, I will develop new formal verification techniques that efficiently compute possible future behaviors---subject to uncertain initial states, inputs, and parameters---within a small time horizon. Just-in-time verification will substantially cut development costs, increase the autonomy of systems (e.g., the range of deployment of automated driving systems), and reduce or even eliminate certain liability claims. The results will be implemented in an open-source software framework and will be primarily demonstrated for automated driving. Successful development of just-in-time verification techniques is yet more challenging than offline verification of autonomous systems, but expected to bring even greater rewards.

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  • Funder: EC Project Code: 804907
    Overall Budget: 1,499,890 EURFunder Contribution: 1,499,890 EUR

    Programming and re-programming robots is extremely time-consuming and expensive, which presents a major bottleneck for new industrial, agricultural, care, and household robot applications. My goal is to realize a scientific breakthrough in enabling robots to learn how to perform manipulation tasks from few human demonstrations, based on novel interactive machine learning techniques. Current robot learning approaches focus either on imitation learning (mimicking the teacher’s movement) or on reinforcement learning (self-improvement by trial and error). Learning even moderately complex tasks in this way still requires infeasibly many iterations or task-specific prior knowledge that needs to be programmed in the robot. To render robot learning fast, effective, and efficient, I propose to incorporate intermittent robot-teacher interaction, which so far has been largely ignored in robot learning although it is a prominent feature in human learning. This project will deliver a completely new and better approach: robot learning will no longer rely on initial demonstrations only, but it will effectively use additional user feedback to continuously optimize the task performance. It will enable the user to directly perceive and correct undesirable behavior and to quickly guide the robot toward the target behavior. In my previous research I have made ground-breaking contributions to the existing learning paradigms and I am therefore ideally prepared to tackle the three-fold challenge of this project: developing theoretically sound techniques which are at the same time intuitive for the user and efficient for real-world applications. The novel framework will be validated with generic real-world robotic force-interaction tasks related to handling and (dis)assembly. The potential of the newly developed teaching framework will be demonstrated with challenging bi-manual tasks and a final study evaluating how well novice human operators can teach novel tasks to a robot.

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  • Funder: EC Project Code: 833548
    Overall Budget: 2,327,550 EURFunder Contribution: 2,327,550 EUR

    How animals’ extraordinarily diverse behaviors have evolved is unknown. Relating interspecific behavioral differences to anatomical or physiological distinctions in neural circuits, and causal genetic variation, offers a powerful approach to inform how nervous systems develop, function and change. Understanding behavioral and nervous system evolution requires deep investment in select species. We propose to establish a new model neurogenetic system: Drosophila sechellia, an island endemic that is closely related to D. melanogaster and D. simulans. While D. sechellia retains global genomic and superficial morphological similarity to its cosmopolitan generalist cousins, this species has adapted to a unique ecological niche, using Morinda fruit as a sole host for feeding and breeding. The project has three aims: Aim 1. Establishment of a D. sechellia (neuro)genetic toolkit: we will build essential genetic reagents for generation and maintenance of animals of desired genotypes, for neurogenetic manipulations, and for recombination mapping-based approaches. Aim 2. Behavioral, neuroanatomical and molecular phenomics: systematic comparison of D. sechellia, D. simulans and D. melanogaster for their behaviors, their neuroanatomy and their neuro-molecular expression properties will reveal how D. sechellia has adapted to its niche, and will provide multiple entry-points to relate molecular, neuronal and behavioral differences between these species. Aim 3. Defining the genetic basis and functional significance of a neuronal adaptation in D. sechellia: through high-resolution mapping and allele swap approaches, we will identify the causal genetic changes underlying a neural adaption in D. sechellia, and its physiological and behavioral significance. This project will establish a powerful new model system for evolutionary neuroscience (and many other fields) and provide fundamental insights into the origins and mechanisms of nervous system and behavioral diversification.

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  • Funder: EC Project Code: 817615
    Overall Budget: 1,985,000 EURFunder Contribution: 1,985,000 EUR

    Advanced ceramics are often combined with metals, polymers or other ceramics to produce structural and functional systems with exceptional properties. Examples are resistors and capacitors in microelectronics, piezo-ceramic actuators in car injection devices, and bio-implants for hip joint replacements. However, a critical issue affecting the functionality, lifetime and reliability of such systems is the initiation and uncontrolled propagation of cracks in the brittle ceramic parts, yielding in some cases rejection rates up to 70% of components production. The remarkable “damage tolerance” found in natural materials such as wood, bone or mollusc, has yet to be achieved in technical ceramics, where incipient damage is synonymous with catastrophic failure. Novel “multilayer designs” combining microstructure and architecture could change this situation. Recent work of the PI has shown that tuning the location of “protective” layers within a 3D multilayer ceramic can increase its fracture resistance by five times (from ~3.5 to ~17 MPa∙m1/2) relative to constituent bulk ceramic layers, while retaining high strength (~500 MPa). By orienting the grain structure, similar to the textured and organized microstructure found in natural systems such as nacre, the PI has shown that crack propagation can be controlled within the textured ceramic layer. Thus, I believe tailored microstructures with controlled grain boundaries engineered in a layer-by-layer 3D architectural design hold the key to a new generation of “damage tolerant” ceramics. This proposal outlines a research program to establish new scientific principles for the fabrication of innovative ceramic components that exhibit unprecedented damage tolerance. The successful implementation of microstructural features (e.g. texture degree, tailored internal stresses, second phases, interfaces) in a layer-by-layer architecture will provide outstanding lifetime and reliability in both structural and functional ceramic devices.

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  • Funder: EC Project Code: 832848
    Overall Budget: 2,500,000 EURFunder Contribution: 2,500,000 EUR

    The four fundamental interactions and their symmetries, the fundamental constants as well as the properties of elementary particles like masses and moments, determine the basic structure of the universe and are the basis for our so well tested Standard Model (SM) of physics. Performing stringent tests on these interactions and symmetries in extreme conditions at lowest energies and with highest precision by comparing e.g. the properties of particles and their counterpart, the antiparticles, will allow us to search for physics beyond the SM. Any improvement of these tests beyond their present limits will require novel experimental techniques. To this end, we propose ambitious Penning-trap based single-ion experiments and measurements of magnetic moments and atomic masses to substantially improve the to-date best limits on some of the key SM predictions. While the measurement technique in determining the eigenfrequencies of the stored particles with unprecedented precision will be identical to the technique used in the past ERC grant by the PI (MEFUCO - MEasurements of FUndamental COnstants), the novel ion preparation and cooling techniques to be developed as well as the physics questions to be addressed are completely different. The new findings will enable us to perform stringent tests of fundamental symmetries like charge-parity-time reversal symmetry (CPT theorem) with (anti)protons or of the energy-mass equivalence principle as well as tests of interactions like quantum electrodynamics in strong fields by using highly charged ions. This will enable us to set new limits on SM predictions or even to reveal their failures. To meet these challenges, advanced charge breeding and cooling techniques will make it possible for us to achieve among other advances a ten-fold improved test of E = mc2, and thus of Einstein’s special theory of relativity and the most stringent CPT test in the baryonic sector by comparing the magnetic moments of the proton and the antiproton.

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  • Funder: FCT Project Code: DL 57/2016/CP1353/CT0005
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1,069 Projects
  • Funder: WT Project Code: 212246
    Funder Contribution: 990,352 GBP

    Membrane proteins destined for lysosomal degradation are ubiquitinated within the endosome and then sorted into intralumenal vesicles (ILVs), to form the multivesicular body (MVB). This critically important process is exemplified by the sorting of EGF receptor (EGFR). MVB sorting requires ESCRTs (Endosomal Sorting Complexes Required for Transport). ESCRTs collectively recognise ubiquitinated EGFR on the cytoplasmic face of the endosome and capture it within ILVs, whilst they escape. Towards understanding how ESCRTs overcome this topological problem, we will reconstitute the process. We have identified all those ESCRTs that drive EGFR sorting, and how they bind each other. We will now reconstitute MVB sorting, using proteoliposomes containing EGFR and exploiting our full complement of baculovirus-expressed ESCRTs. We will use site-directed photo-crosslinking to map the entire process biochemically, and will complement this with further in vitro analysis of the molecular architecture within the developing ILV. Key conclusions will be verified in cells. Current ideas suggest ubiquitination is the determining factor for EGFR sorting. However, we believe instead that EGFR signalling-dependent activation of ESCRTs is decisive. We will systematically identify ESCRT post-translational modifications (PTMs) that map with MVB sorting, and test using both reconstituted proteoliposomes and in cells how these PTMs control the pathway. Plasma membrane proteins destined for degradation are internalised, enter the endosome, and then transit to the lysosome. Many crucial proteins follow this pathway, with epidermal growth factor receptor (EGFR) an exemplar because of its biological and biomedical importance. EGFR transport to the lysosome requires a crucial event; the receptor is ubiquitinated and then enters membrane vesicles that bud into the lumen of the endosome, to form the multivesicular body. The molecular machinery that drives multivesicular body formation must overcome a complex topological problem: it recognises ubiquitinated EGFR on the cytoplasmic face of the endosome, generates vesicles that capture EGFR inside the endosome, but escapes itself. How this works remains mysterious, but we aim to solve it. We will reassemble the machinery from its component parts on artificial endosomes, and dissect biochemically how it envelops EGFR. We will also examine how the machinery is activated by EGFR, ensuring EGFR’s efficient capture.

    more_vert
  • Funder: EC Project Code: 818858
    Overall Budget: 2,000,000 EURFunder Contribution: 2,000,000 EUR

    For many years, lymphatic vessels have been viewed as inert fluid conduits whose open structure allows for passive flow of antigens, proteins and cells from peripheral tissues to lymphoid organs. Yet, recent discoveries highlighting novel functions and heterogeneous origins of the lymphatic endothelium, call for reevaluation of the passive lymphatic-vessel paradigm. During the past decade, we have used the zebrafish (ZF) to detail the cellular and molecular events underlying the development of the lymphatic system. Our discoveries have greatly contributed to our understanding of the origins, specification and mechanisms of formation of lymphatic endothelial cells (LECs) in the developing embryo. In line with our past achievements, we now aim towards novel directions- to transform the adult ZF into an equally convenient model for the study of lymphatic diversity. The overall goal of LymphMap is to reveal the multiple regulatory levels that coordinate the formation and functionality of lymphatic vessels in health and disease. To this end, we will carry out a comprehensive research program characterizing four distinct aspects of lymphatic biology: 1.Cellular origins and molecular signature of LECs 2.Formation and specialization of organotypic lymphatics 3.Lymphatic vessels during organ regeneration 4.Lymphatic involvement in human disease Our experimental strategy involves the combination of high-resolution imaging, global expression profiling and regeneration models in adult ZF, with analyses of human-derived LECs in various clinical settings. The important and unique aspects of our approach are the focus on in vivo dynamics, and the cross-organ comparative analysis, which will likely provide the much-needed knowledge on lymphatic diversity in health and disease. When completed, we anticipate that this work will be part of a new paradigm – no longer perceiving lymphatics as passive bystanders, but rather as orchestrators of tissue morphogenesis and regeneration.

    more_vert
  • Funder: EC Project Code: 833801
    Overall Budget: 2,164,240 EURFunder Contribution: 2,164,240 EUR

    Quantum simulators (QS) are experimental systems that allow mimic hard to simulate models of condensed matter, high energy physics and beyond. QS have various platforms: from ultracold atoms and ions to superconducting qubits. They constitute the important pillar of quantum technologies (QT), and promise future applications in chemistry, material science and optimization problems. Over the last decade, QS were particularly successful in mimicking topological effects in physics (TEP) and in developing accurate quantum validation/certification (QVC) methods. NOQIA is a theory project, aimed at introducing the established field of QS+TEP+QVC into two novel areas: physics of ultrafast phenomena and attoscience (AS) on one side, and quantum machine learning (ML) and neural networks (NN) on the other. This will open up new horizons/opportunities for research both in AS and in ML/NN. For instance, in AS we will address the question if intense laser physics may serve as a tool to detect topological effects in solid state and strongly correlated systems. We will study response of matter to laser pulses carrying topological signatures, to determine if they can induce topological effects in targets. We will design/analyze QS using trapped atoms to understand and detect TEP in the AS. On the ML/NN side, we will apply classical ML to analyze, design and control QS for topological systems, in order to understand and optimize them. Conversely, we will transfer many-body techniques to ML in order to analyze and possibly improve performance of classical machine learning. We will design and analyze quantum neural network devices that will employ topology in order to achieve robust quantum memory or information processing. We will design/study attractor neural networks with topological stationary states, or feed-forward networks with topological Floquet and time-crystal states. Both in AS and ML/NN, NOQIA will rely on quantum validation and certification protocols and techniques.

    visibility2K
    visibilityviews2,237
    downloaddownloads4,257
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    more_vert
  • Funder: EC Project Code: 788851
    Overall Budget: 2,498,530 EURFunder Contribution: 2,498,530 EUR

    NEMO, NEtwork MOtion, is an inter-disciplinary proposal centered on network dynamics. The inter-disciplinarity spans from communication engineering to mathematics, with an innovative interplay between the two. NEMO’s focus is on stochastic geometry. This emerges as one of the most important new conceptual and operational tools of the last 10 years in wireless networking, with a major academic and industrial impact on architecture, protocol design, planning and economic analysis. Nevertheless, the state of the art is unable to cope with the dynamics introduced in recent and future network functionalities. NEMO’s aim is to introduce dynamics in wireless stochastic geometry. The dynamic versions of stochastic geometry to be developed will capture these new functionalities and specifically tackle two core promises and challenges of the future of wireless networking: that of ultra-low latency networking, required for enabling the unfolding of future real time interactions, and that of draining to the Internet the unprecedented amount and structure of data stemming from the Internet of Things. Several fundamental types of random network dynamics underpinning these functionalities are identified. General mathematical tools combining stochastic geometry, random graph theory, and the theory of dynamical systems will be developed to analyze them. This will provide parametric models mastering the complexity of such networks, which will be instrumental in addressing the above challenges. The aim is to have, through these dynamical versions, the same academic and industrial impact on wireless networks as static stochastic geometry has today. NEMO will leverage structural interactions of INRIA with Ecole Normale Supérieure on the mathematical side, and with Nokia Bell Labs and Orange on the engineering side. This will create in Europe a group focused on this mathematics-communication engineering interface, and to become the top innovation group of the field worldwide.

    more_vert
  • Funder: EC Project Code: 817629
    Overall Budget: 1,999,080 EURFunder Contribution: 1,999,080 EUR

    Engineers and computer scientists are currently developing autonomous systems whose entire set of behaviors in future, untested situations is unknown: How can a designer foresee all situations that an autonomous road vehicle, a robot in a human environment, an agricultural robot, or an unmanned aerial vehicle will face? Keeping in mind that all these examples are safety-critical, it is irresponsible to deploy such systems without testing all possible situations---this, however, seems impossible since even the most important possible situations are unmanageably many. I propose a paradigm shift that will make it possible to guarantee safety in unforeseeable situations: Instead of verifying the correctness of a system before deployment, I propose just-in-time verification, a new, to-be-developed verification paradigm where a system continuously checks the correctness of its next action by itself in its current environment (and only in it) in a just-in-time manner. Since future autonomous systems will have a tight interconnection of discrete computing and continuous physical elements, also known as cyber-physical systems, I will develop just-in-time verification for this system class. In order to prove correct behavior of cyber-physical systems, I will develop new formal verification techniques that efficiently compute possible future behaviors---subject to uncertain initial states, inputs, and parameters---within a small time horizon. Just-in-time verification will substantially cut development costs, increase the autonomy of systems (e.g., the range of deployment of automated driving systems), and reduce or even eliminate certain liability claims. The results will be implemented in an open-source software framework and will be primarily demonstrated for automated driving. Successful development of just-in-time verification techniques is yet more challenging than offline verification of autonomous systems, but expected to bring even greater rewards.

    visibility7
    visibilityviews7
    downloaddownloads5
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    more_vert
  • Funder: EC Project Code: 804907
    Overall Budget: 1,499,890 EURFunder Contribution: 1,499,890 EUR

    Programming and re-programming robots is extremely time-consuming and expensive, which presents a major bottleneck for new industrial, agricultural, care, and household robot applications. My goal is to realize a scientific breakthrough in enabling robots to learn how to perform manipulation tasks from few human demonstrations, based on novel interactive machine learning techniques. Current robot learning approaches focus either on imitation learning (mimicking the teacher’s movement) or on reinforcement learning (self-improvement by trial and error). Learning even moderately complex tasks in this way still requires infeasibly many iterations or task-specific prior knowledge that needs to be programmed in the robot. To render robot learning fast, effective, and efficient, I propose to incorporate intermittent robot-teacher interaction, which so far has been largely ignored in robot learning although it is a prominent feature in human learning. This project will deliver a completely new and better approach: robot learning will no longer rely on initial demonstrations only, but it will effectively use additional user feedback to continuously optimize the task performance. It will enable the user to directly perceive and correct undesirable behavior and to quickly guide the robot toward the target behavior. In my previous research I have made ground-breaking contributions to the existing learning paradigms and I am therefore ideally prepared to tackle the three-fold challenge of this project: developing theoretically sound techniques which are at the same time intuitive for the user and efficient for real-world applications. The novel framework will be validated with generic real-world robotic force-interaction tasks related to handling and (dis)assembly. The potential of the newly developed teaching framework will be demonstrated with challenging bi-manual tasks and a final study evaluating how well novice human operators can teach novel tasks to a robot.

    visibility82
    visibilityviews82
    downloaddownloads280
    Powered by Usage counts
    more_vert
  • Funder: EC Project Code: 833548
    Overall Budget: 2,327,550 EURFunder Contribution: 2,327,550 EUR

    How animals’ extraordinarily diverse behaviors have evolved is unknown. Relating interspecific behavioral differences to anatomical or physiological distinctions in neural circuits, and causal genetic variation, offers a powerful approach to inform how nervous systems develop, function and change. Understanding behavioral and nervous system evolution requires deep investment in select species. We propose to establish a new model neurogenetic system: Drosophila sechellia, an island endemic that is closely related to D. melanogaster and D. simulans. While D. sechellia retains global genomic and superficial morphological similarity to its cosmopolitan generalist cousins, this species has adapted to a unique ecological niche, using Morinda fruit as a sole host for feeding and breeding. The project has three aims: Aim 1. Establishment of a D. sechellia (neuro)genetic toolkit: we will build essential genetic reagents for generation and maintenance of animals of desired genotypes, for neurogenetic manipulations, and for recombination mapping-based approaches. Aim 2. Behavioral, neuroanatomical and molecular phenomics: systematic comparison of D. sechellia, D. simulans and D. melanogaster for their behaviors, their neuroanatomy and their neuro-molecular expression properties will reveal how D. sechellia has adapted to its niche, and will provide multiple entry-points to relate molecular, neuronal and behavioral differences between these species. Aim 3. Defining the genetic basis and functional significance of a neuronal adaptation in D. sechellia: through high-resolution mapping and allele swap approaches, we will identify the causal genetic changes underlying a neural adaption in D. sechellia, and its physiological and behavioral significance. This project will establish a powerful new model system for evolutionary neuroscience (and many other fields) and provide fundamental insights into the origins and mechanisms of nervous system and behavioral diversification.

    visibility5
    visibilityviews5
    downloaddownloads5
    Powered by Usage counts
    more_vert
  • Funder: EC Project Code: 817615
    Overall Budget: 1,985,000 EURFunder Contribution: 1,985,000 EUR

    Advanced ceramics are often combined with metals, polymers or other ceramics to produce structural and functional systems with exceptional properties. Examples are resistors and capacitors in microelectronics, piezo-ceramic actuators in car injection devices, and bio-implants for hip joint replacements. However, a critical issue affecting the functionality, lifetime and reliability of such systems is the initiation and uncontrolled propagation of cracks in the brittle ceramic parts, yielding in some cases rejection rates up to 70% of components production. The remarkable “damage tolerance” found in natural materials such as wood, bone or mollusc, has yet to be achieved in technical ceramics, where incipient damage is synonymous with catastrophic failure. Novel “multilayer designs” combining microstructure and architecture could change this situation. Recent work of the PI has shown that tuning the location of “protective” layers within a 3D multilayer ceramic can increase its fracture resistance by five times (from ~3.5 to ~17 MPa∙m1/2) relative to constituent bulk ceramic layers, while retaining high strength (~500 MPa). By orienting the grain structure, similar to the textured and organized microstructure found in natural systems such as nacre, the PI has shown that crack propagation can be controlled within the textured ceramic layer. Thus, I believe tailored microstructures with controlled grain boundaries engineered in a layer-by-layer 3D architectural design hold the key to a new generation of “damage tolerant” ceramics. This proposal outlines a research program to establish new scientific principles for the fabrication of innovative ceramic components that exhibit unprecedented damage tolerance. The successful implementation of microstructural features (e.g. texture degree, tailored internal stresses, second phases, interfaces) in a layer-by-layer architecture will provide outstanding lifetime and reliability in both structural and functional ceramic devices.

    visibility74
    visibilityviews74
    downloaddownloads145
    Powered by Usage counts
    more_vert
  • Funder: EC Project Code: 832848
    Overall Budget: 2,500,000 EURFunder Contribution: 2,500,000 EUR

    The four fundamental interactions and their symmetries, the fundamental constants as well as the properties of elementary particles like masses and moments, determine the basic structure of the universe and are the basis for our so well tested Standard Model (SM) of physics. Performing stringent tests on these interactions and symmetries in extreme conditions at lowest energies and with highest precision by comparing e.g. the properties of particles and their counterpart, the antiparticles, will allow us to search for physics beyond the SM. Any improvement of these tests beyond their present limits will require novel experimental techniques. To this end, we propose ambitious Penning-trap based single-ion experiments and measurements of magnetic moments and atomic masses to substantially improve the to-date best limits on some of the key SM predictions. While the measurement technique in determining the eigenfrequencies of the stored particles with unprecedented precision will be identical to the technique used in the past ERC grant by the PI (MEFUCO - MEasurements of FUndamental COnstants), the novel ion preparation and cooling techniques to be developed as well as the physics questions to be addressed are completely different. The new findings will enable us to perform stringent tests of fundamental symmetries like charge-parity-time reversal symmetry (CPT theorem) with (anti)protons or of the energy-mass equivalence principle as well as tests of interactions like quantum electrodynamics in strong fields by using highly charged ions. This will enable us to set new limits on SM predictions or even to reveal their failures. To meet these challenges, advanced charge breeding and cooling techniques will make it possible for us to achieve among other advances a ten-fold improved test of E = mc2, and thus of Einstein’s special theory of relativity and the most stringent CPT test in the baryonic sector by comparing the magnetic moments of the proton and the antiproton.

    more_vert
  • Funder: FCT Project Code: DL 57/2016/CP1353/CT0005
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