There will be around 35 million private or non-industrial use robots in the world by 2018, a market of 19 billion euros. However, autonomous robot technology in Europe is not yet ready to lead this high expectancy due to the lack of robust functionality in uncertain environments. Particularly, safe interaction is an essential requirement. A basic skill, still unachieved, is to allow the robot to be aware of its own body and perceive other agents. Recent evidence suggests that self/other distinction will be a major breakthrough for improving interaction and might be the connection between low-level sensorimotor abilities and conceptual interpretation. Advanced sensorimotor learning combined with new multimodal sensing devices, such as artificial skin, makes now possible that the robot acquires its perceptual representation, and I hypothesize that learning the multisensory-motor spatiotemporal contingencies permits self/other distinction. Hence, the aim of the project is to provide a hierarchical probabilistic model for self/other distinction in robots, learning the sensorimotor contingencies during interaction. This model not only provides a holistic solution for building the perceptual schema and improves interaction under uncertainty but it might also give insights about how humans construct their own perceptual representation and the sense of agency. Finally, the model will be tested in a whole body sensing humanoid and validated in a service robot in collaboration with a robotics SME. I will use an interdisciplinary approach that combines probabilistic and information sciences modelling with cognitive psychology, creating a highly attractive career profile. SELFCEPTION will boost the materialization of the next generation of perceptive robots: multisensory machines able to build their perceptual body schema and distinguish their actions from other entities. We already have robots that navigate and now it is the time to develop robots that interact.
Arbuscular mycorrhiza (AM) is an ancient plant-fungus symbiosis that is wide-spread in the plant kingdom. AM improves plant nutrition, stress resistance and general plant performance and thus represents a promising addition to sustainable agricultural practices. Mineral nutrients are released from the fungus to the plant at highly branched hyphal structures, the arbuscules, which form inside root cortex cells. Like the cells of other multicellular eukaryotes, plant cells show a remarkable developmental plasticity. Single cell re-differentiation is a fascinating process during arbuscule development, which can be conceptually separated into distinct stages controlled by the plant cell which precisely guide the step-wise formation of different parts of the arbuscule. It involves cell autonomous transcriptional reprogramming and subcellular remodelling, leading to repositioning of subcellular structures, cell polarization and multiplication of organelles. It is currently unknown how cell-autonomous reprogramming during arbuscule development is regulated. RECEIVE utilizes an integrated strategy combining transcriptional profiling, transcription factor identification, interaction network analysis with reverse genetics and cell biological techniques to understand the coordinated step-wise progression of arbuscule development. RECEIVE builds on the hypothesis that each stage of arbuscule development is accompanied by a stage-specific wave of gene expression and that transcriptional regulation is a key determinant of the developmental progress from stage to stage. The characterisation of these waves and the identification of the underlying transcriptional regulatory nodes is the focus of this project. RECEIVE aims to bridge a major knowledge gap about the molecular basis of one of the most important symbioses on earth.
ν-cleus will be a new multi-purpose table-top experiment aimed at the first exploration of coherent neutrino-nucleus scattering (CNNS) at a nuclear power reactor. Our novel detector technology will achieve an unprecedentedly high sensitivity to new physics within and beyond the Standard Model of Particle Physics, with an enormous discovery potential. The new method is not only complementary to competing approaches, but superior in terms of performance, cost and size. The ultra-low threshold character of my experiment will allow a determination of the Weinberg angle at MeV-scale momentum transfers and the first direct search for eV-scale sterile neutrinos via CNNS. We will significantly improve the sensitivity for a neutrino magnetic dipole moment, unravel anomalies in the reactor antineutrino spectrum and test new models for exotic neutral currents. My research on gram-scale cryogenic calorimeters (gramCCs) has resulted in a recent breakthrough: we achieved the world-best energy threshold for nuclear-recoils of 19.7eV, one order of magnitude lower than for previous detectors. I propose to operate gramCCs within a fiducial-volume cryogenic detector. This completely new detector concept is suited for an above-ground operation of excellent performance while backgrounds are significantly suppressed. Located at a nuclear power reactor ν-cleus will achieve a signal-to-background ratio of ~10^3 - a unique situation in neutrino physics. This will enable a rapid discovery of CNNS within a few weeks. ν-cleus will have enormous impact on modern physics and future technologies. It will be a prototype for next-generation, high-precision solar neutrino experiments and guarantees a technological spin-off for reactor safeguards and non-proliferation measures. With this ERC grant I will set up a high-class research team with world-leading expertise in cryogenic detectors and low-background techniques, which will ensure Europe’s role as a pioneer in this new field.