Grants

My research project is driven by the question: What are nature’s fundamental building blocks, i.e., the constituents of matter and the quantum structure of spacetime? A central novelty of my project is my hypothesis that the interplay of matter and quantum gravity holds the key to the answer. I will test whether a powerful symmetry principle, scale-invariance, sets in at tiny distances close to the Planck sale, making quantum gravity with matter an asymptotically safe theory. My research methodology employs a mathematical version of a microscope, the Renormalization Group. Its use in two approaches to quantum gravity is a stand-out feature of my project. This will enable me to push the boundaries of the field by mapping the phase diagram of quantum gravity with matter, and bridging the gap to particle physics. I will discover whether quantum gravity and the Standard Model are asymptotically safe and for the first time explore the nature of dark matter in the asymptotic-safety paradigm.

The goal of INNATE is to propose a fundamentally new paradigm of adaptive machines that can continually learn from experiences and apply previously learned knowledge to novel situations. Artificial Intelligence (AI) methods are becoming part of our daily and can now outperform humans in many domains. However, these systems still pale in comparison to even simple biological intelligence, which can learn and adapt to unforeseen experiences. Current machine learning systems can only deal with situations they have been trained for in advance; they are unable to adapt during execution to unexpected events. Organisms in nature can react quickly to changes because they have evolved innate priors that reflect properties of the physical world. Here we will develop a new class of algorithms based on a combination of evolutionary computation and state-of-the-art reinforcement learning, which will significantly extend the usefulness of robots in manufacturing and warehouse automation.

Tiny population. Huge territory. Extreme conditions. It is far from obvious where to find inspiration when Greenland aims for independence. Scholarship trapped between idiographic detail and unreflexive insertion in theoretical categories leaves us no clear image of how a wide variety of im- and explicit comparisons in political debate, public policy, and scholarly analysis configure how Greenland imagines independence. Through a close reading of current and historical texts on core developmental sectors, IMAGINE PoCo shows how application, rejection and forgetting of categories for comparison closes off some futures, making others self-evident. Combining insights from late imperialism and early decolonization with International Political Sociology approaches to identity, it advances our understanding of an understudied case, central for a reconfigured Arctic; theorizes the politics of comparison in the negotiation of collective identity; and opens up a new comparative research agenda.

Stacking two-dimensional (2D) materials in van der Waals heterostructures offers unlimited possibilities for tailoring quantum states and inducing new electronic properties. In this project, I will systematically generate such heterostructures by combining 2D material growth and transfer methods that can produce stacks with arbitrary material combinations and tuneable interlayer twist angles. The quantum states of these stacks will be determined at my new facility for angle-resolved photoemission spectroscopy experiments with nanoscale spatial resolution (nanoARPES) at the ASTRID2 light source at Aarhus University. I will extend the capabilities of this setup to enable in operando measurements of functioning heterostructures integrated in electrical devices, which will unveil how the structure of the materials correlates with their electronic structure and how these properties are modified in the presence of current or electrostatic doping.

A large proportion of trees and shrubs are located outside of forests in peri-urban and rural dryland areas, playing a crucial role for the stability of the ecosystems, biodiversity, and providing food resources and shelter for humans and animals. However, no large scale assessment on individual trees and their density outside of forests exists. Here, this project applies deep learning on sub-meter resolution satellite imagery at continental scale, to map each woody plant and its characteristics (e.g. density, crown size) in hyper-arid, arid and semi-arid Africa, with a specific focus on the Sahara and Sahel. Furthermore, the environmental and social factors that determine the distribution, characteristics and functions of each tree and shrub are analyzed. Results will be stored in a publicly available spatial data-base including each woody plant outside forests in Africa, which is pivotal to understand their role in ecology, as carbon stocks, agroforestry, and in people’s livelihoods.

Migration and Membership Regimes in the Ancient Greek World (c. 400 BCE-100 CE) aims at providing a new comprehensive framework for the study of ancient Greek migration in the Hellenistic period (broadly conceived). In contrast with earlier scholarship, which mostly confined itself to juridical aspects of foreigner status, the project departs from the assumption that legal, social, economic and religious aspects of host communities should be viewed as integral parts of a 'membership regime' which profoundly shaped outcomes for migrants as well as citizens. The project consist of four case studies each probing different aspect of different membership regimes: (1) the social means by which wealthy foreigners assimilated with local civic elites, (2) the social and economic integration of former slaves, (3) the negotiation of status fragility of free foreigners in the economy, politics and religion, and (4) women's agency in the cult of foreign gods.

Small RNA-mediated transposon silencing in animals occurs via Piwi protein effector complexes guided by Piwi-interacting small RNAs (piRNAs). The piRNA pathway is thus part of a genetic conflict between the host genome and genetic parasites in the form of transposons. With this work, I will uncover mechanistic insight into how transposons and animal genomes co-evolve and reveal the molecular ‘weapons’ and consequences of the on-going genetic arms race. To do this, I will use the heterochromatic expression pathways of Drosophila piRNA source loci as a novel model system for mechanistic understanding of genetic conflicts. With this system, I will apply proteomics, genetic screen, evolutionary analyses, and high-throughput protein interaction assay to identify the molecular mechanisms employed by transposons to evade piRNA-mediated silencing and further to uncover how the piRNA pathway factors, in turn, adapt in the constant arms race between the host genome and transposons.

Intelligent machines that understand natural language texts are the Holy Grail of AI. If achieved, it can automatically extract useful information from big messy text collections. Many challenges must be overcome first. To alleviate the scarcity of resources and broaden the scope to Danish and other small languages, I will unify two strands of research, transfer learning and weak supervision, with the aim to design cross-domain and cross-lingual algorithms that extract information more robustly under minimal guidance (for two applications: syntactic parsing and information extraction). Besides existing benchmarks, the designed technology is tested in production on job skills text data provided by "Styrelsen for Arbejdsmarked og Rekruttering". Resulting prototypes will be made publicly available to accelerate innovation in the use of linguistic data for knowledge discovery.

Glioblastoma multiforme (GBM) is a highly aggressive, universally fatal brain tumor, for which no efficient treatments exist. The compound [125I]iododeoxyuridine (125I-UdR) was recently shown to be highly effective against GBM in rats, even curing animals in some cases. 125I-UdR kills cancer cells by inserting into the DNA and emitting a burst of highly destructive Auger electrons. When tested in pigs however, 125I-UdR rapidly washed out of the brain, due to the larger brain size. This ruled out translation to humans. In this project, we will develop nanocarrier systems for delivering 125I-UdR againt GBM. Such systems can distribute and be retained efficiently by convection enhancded delivery (CED) in brain tissue, solving the problem of wash-out. In addition, we will design systems for releasing free and unmodified 125I-UdR after distribution in the brain. This is because the uptake of 125I-UdR into DNA is enzymatic. With this, we will develop a new therapy and potential cure for GBM.

Animals must continuously adapt to osmotic challenges to maintain homeostasis and to survive. This requires the coordinated actions of organs with specialized functions, which in turn are modulated by systemic signals communicated by other organs to ensure an appropriate physiological response by the organisms. Molecular osmoreceptors lie at the heart of the central mechanisms coordinating these processes. Yet, the molecular identity of such osmosensitive molecules, and how they modulate the release of known neuroendocrine factors that control systemic osmoregulation is unknown. Using the genetic model organism, Drosophila melanogaster, in combination with cutting-edge technologies in Next-Gen Sequencing (NGS), quantitative mass-spectrometry, neuroendocrinology, genetics, advanced bioimaging, this research program will achieve a paradigm shift in our understanding of the molecular, cellular and network mechanisms that mediate systemic osmoregulation in the largest animal group on Earth