One of the most fundamental challenges in the digital age is to automatically create accurate, high-quality 3D representations of the world around us. This would have far-reaching impact, from enabling advances entertainment and immersive technologies (e.g., mixed reality) to medical applications and industrial manufacturing pipelines. Despite remarkable progress in scanning devices and 3D reconstruction algorithms, the resulting models remain highly impractical for display or use in virtual environments. This is due to the limited quality of these reconstructed 3D models, which is still far from the quality of assets designed by professional artists in countless of working hours. We believe that the key to addressing these shortcomings is understanding the design process of artist-created assets. We can then learn the correlation to real-world observations and replicate the process conditioned on these real-world input scans. In this proposal, we will answer the question "How can we turn 3D scans into CAD-quality 3D assets?".

Fortschritte in der künstlichen Intelligenz haben zur Entwicklung autonomer Agenten (Autos, Boote, Drohnen) geführt, die in einer dynamischen, offenen Umgebung agieren. Wie durch öffentlichkeits\-wirk\-same Unfälle deutlich wurde, bleibt es eine große Herausforderung, deren Sicherheit zu gewährleisten. In diesem Projekt schlagen wir eine zertifizierbare Sicherheitsebene vor, die Entscheidungen im Voraus überwacht und korrigiert. Der Ansatz basiert auf mathematisch rigorosen Techniken aus den formalen Methoden, einer Disziplin der Informatik, die in der Software-Industrie fest etabliert ist und auch in anderen Bereichen, wie z.B. bei cyber-physischen Systemen, immer mehr an Bedeutung gewinnt. Diese Überwachung verhindert nicht nur Unfälle, sondern führt auch zu schnelleren und sichereren Trainingszyklen, da sie zusätzliche Trainingsdaten aus automatisch generierten Familien von kritischen Trajektorien generieren kann. Verwandte Ansätze verwenden Optimierungsverfahren, die aufgrund von Erfüllbarkeitsproblemen, numerischen Fehlern oder hohen Rechenkosten möglicherweise keine gültige Lösung liefern. Im Gegensatz dazu kann unser Ansatz sowohl mathematisch als auch numerisch korrekt und mit vorhersagbaren, niedrigen Laufzeiten implementiert werden. Wir vergleichen unseren Ansatz mit verwandten State-of-the-Art-Ansätzen aus der modellprädiktiven Steuerung und der datenbasierten Vorhersage, indem wir rigorose statistische Tests an realen Systemen durchführen - darunter zwei verschiedene Arten von autonomen Autos, ein Boot und ein Manipulator. Um den Ansatz für zukünftige Generationen von Systemen zugänglich zu machen, bei denen es zunehmend schwieriger wird, Modelle zu erhalten, werden wir untersuchen, inwieweit datenbasierte Ansätze integriert werden können, ohne die Sicherheit und Leistung zu beeinträchtigen. Das vorgeschlagene dreijährige Programm ermöglicht es ENSTA und TUM, ihre wissenschaftliche Expertise und experimentellen Plattformen zu teilen und eine langfristige Zusammenarbeit auf Basis einer gemeinsamen Strategie für vertrauenswürdige Autonomie aufzubauen.

Humans are microbial, living in close functional interaction with their skin and mucosal microbiomes. Human-microbes interplay has proven essential for the maintenance of health and well-being and profiling of microbiomes will become an essential feature of the personalized preventive nutrition and medicine of tomorrow. Europe has gained a leading position in microbiome science and yet to fulfill societal expectations, an international consensus will be essential on key aspects. These include i) clinical trial design as well as analytical standards, ii) definitions of healthy microbiomes as a function of numerous factors, accounting for confounders, iii) means of demonstrating causality of altered host-microbes interactions in diseases and iv) processes for the development of clinically relevant, validated biomarkers. The International Human Microbiome Concertation and Support Action (IHMCSA) will tackle all necessary steps to open the perspective of managing nutrition and health of the microbial human. Involving key stakeholders representing the multiplicity of actors concerned, including citizens, IHMCSA will map existing material, delineate necessary steps and pathways for innovation and build consensus on priorities and means for the future of microbiome science and its translation. This will lead to recommendations, validated by an international Strategic Steering Committee as well as academies of medicine of the world, directed to the European Commission, international research programmes, funding and regulatory agencies and decision makers of health systems. To ensure sustainability of the proposed measures, IHMCSA will promote unified repositories for sharing standards, SOPs and data, and contribute to the structuration of the European Microbiome Centers Consortium with a role in gathering world microbiome networks of excellence. With IHMCSA, human-associated microbiomes will be recognized for their true value in contributing to secure the future of mankind.

The interplay of correlations and quantum fluctuations in condensed matter can give rise to topological phases with unexpected and exciting properties. While originally proposed for fractional quantum Hall states, recently new opportunities arose for realizing and controlling topological order: Quantum computers have demonstrated the fascinating fractionalized statistics of topological excitations and moiré semiconductors have appeared as promising candidates for realizing topological order. However, it remains an important open challenge to understand the dynamical response of such entangled matter, both on the fundamental level as well as for providing key experimental signatures that characterize these phases. The central focus of the project DynaQuant is to develop new concepts and new theoretical methods to study the dynamical response of topological quantum states. The project has three principal objectives each of which would represent a major contribution to the field: (O1) To introduce new dynamical probes tailored toward emerging experimental platforms that enable the detection of unique signatures of equilibrium phases with topological order. (O2) To demonstrate the response of pristine nonequilibrium phases with Floquet topological order that do not possess analogues in thermal equilibrium. (O3) To develop novel tensor network approaches for fracton topological order and investigate the collective dynamics of their excitations. To successfully meet our ambitious objectives, my team and I will develop complementary analytical and numerical approaches. This allows us to understand fundamental dynamical properties of entangled quantum matter and to guide future experiments. Due to the international effort in developing experimental platforms for realizing topological order, it is now the right time to foster a deep understanding of their dynamical response, which is the central goal of the project DynaQuant.

The CONDUCTOR project’s main goal is to design, integrate and demonstrate advanced, high‐level traffic and fleet management that will allow efficient and globally optimal transport of passengers and goods, while ensuring seamless multi‐modality and interoperability. Using innovative dynamic balancing and priority‐based management of vehicles (automated and conventional) CONDUCTOR will build upon state-of-the-art fleet and traffic management solutions in the CCAM ecosystem and develop next generation simulation models and tools enabled by machine learning and data fusion, enhancing the capabilities of transport authorities and operators, allowing them to become “conductors” of future mobility networks. We will upgrade existing technologies to place autonomous vehicles at the centre of future cities, allowing heightened safety and flexible, responsive, centralized control able to conduct traffic and fleets at a high level. These innovations will lead to less urban traffic and congestion, lowered pollution, and a higher quality of life. Project innovations will be integrated into a common, open platform, and validated in three use cases, testing the interoperability of traffic management systems and integration of different transportation means for both people and goods. Use case UC1 integrates traffic management with inter-modality, UC2 tests demand-response transport, and UC3 urban logistics. In each use case and its demonstrations, simulations will be validated through real life data.