The Helmholtz Association's research fields tackle the major challenges and pressing issues facing society and develop sustainable solutions for tomorrow and beyond. As an enabler, Helmholtz AI will transfer methods of applied AI in all of these six research fields:
The scientists involved in aeronautics, space and transport research address the major challenges of society in the fields of mobility, information systems, communication, resource management, the environment and safety.
A high potential for AI applications in aeronautics, space and transport lies in the topics autonomous driving, traffic research and aeronautics, although there are many other interesting fields of application, such as earth observation, safety-critical systems, automated and networked driving, personal assistants and expert systems, robotics, production, predictive maintenance and condition monitoring.
The recent technical innovations in the fields of artificial intelligence and machine learning provide excellent opportunities to address challenges in Earth system analytics and modelling. Approaches such as hybrid modelling, incorporating AI techniques into existing physics-driven models, advanced data assimilation, and pattern and interference recognition, appear promising to improve the quality of model results and address challenges pertaining to the ever-increasing model resolution and computational demand that comes with it.
First examples for applications benefitting from the new techniques include, for instance, innovation on model parametrizations to model sub-scale processes or classification of cloud formations and other naturally occurring patterns.
A high potential for AI applications in energy research lies in solutions for future energy systems. They are increasingly based on decentralized power generation, ‘prosumers’, decentralized energy storage and delocation of large-scale power sources (e.g. offshore wind parks). At the same time, future energy system have to deal with e-mobility and smart homes comprising roof-top photovoltaics and heat pumps. Hence, the current rigid model of energy distribution is no longer suitable for these changing preconditions and requirements; autonomous decisions are needed in management, operation and optimization. AI methods for, e.g., energy forecasting as well on the supply and demand side, must therefore be adapted for this ever increasing application domain and a tight integration of AI in the energy system design is needed.
Artificial intelligence (AI) has the potential to help address important health challenges, and it is in fact already being used or trialled for a range of healthcare and research purposes. As an incredibly powerful tool to analyse and identify patterns in large and complex datasets faster and more precisely than has previously been possible, it can also be used to search the scientific literature for relevant studies, and to combine different kinds of data; for example, to aid drug discovery. AI systems used in healthcare could also be valuable for medical research by helping to analyse relationships between prevention or treatment techniques and patient outcomes, and match suitable patients to clinical studies. The use of AI in health, however, raises ethical issues, which is why another key challenge is to ensure that AI is developed and used in a way that is transparent and compatible with the public interest, whilst stimulating and driving innovation in the sector.
The researchers in the research field key technologies explore and develop generic technologies that contribute to the future viability of our society. The research field addresses key scientific topics that will provide innovative impulses in the three major areas of the research field: information technology, materials sciences and life sciences.
Information-oriented research is becoming increasingly important concerning the digitization of science, business, and society. The Helmholtz Association addresses this development by performing integral research on conceptual, technical, and sociological aspects of information. Digitization affects all levels of society and requires a transformation of science. Research covers the complete spectrum from basic research to application, following a multi-disciplinary approach.
Researchers on the structure of matter explore the building blocks of matter and the forces operating between them at a wide range of levels, from elementary particles to complex functional materials to gigantic objects and structures in the universe.
An important part of this work entails the development of new technological concepts for fields such as particle acceleration, detector systems and the optimization of high-performance computing and data storage that pave the way for the application of these technologies, enabling them for the world of tomorrow.