Here you will find an overview of the projects we are currently funding. On average, about 250 projects are being funded. Smaller funding projects are sometimes not described individually.
256
ongoing projects
Prof. Dr. Pascal Laube is researching the use of dialog-oriented multi-agent systems in project management in the “Intelligent Agents in Dialogue” project at Furtwangen University. The aim is to optimize communication and resource allocation.
Whether and how are degradable materials possible? To clarify this question, research is being conducted into intelligent materials with embedded microphases that promote colonisation by microorganisms in water bodies and thus trigger their complete degradation.
Prof. Dr. Tilman Traub, Professor of Automation Technology in Manufacturing at Aalen University, is researching the development of AI assistance systems for small series and special processes that are trained using the knowledge of experienced employees.
The project is developing new therapeutic approaches for the regenerative treatment of neurological diseases such as multiple sclerosis. The aim is to use interactive synthetic biomaterials.
A research training group is investigating how conclusions are drawn in machine learning, taking into account the uncertainties involved.
The Albstadt-Sigmaringen University of Applied Sciences integrates aspects of sustainability into compulsory and optional engineering courses. Interdisciplinary courses are designed to impart skills for holistic, sustainable product development.
Dr. Lina Jaurigue conducts research in the fields of nonlinear dynamics and reservoir computing. She studied physics at Victoria University of Wellington and then completed her doctorate at TU Berlin. She has been a postdoctoral researcher at TU Ilmenau since 2022.
JenaVersum is a network for the cooperation of actors from science and industry in the Jena region. The development of a database should enable a coordinated use of the available research equipment for all partners.
Powerful AI models require a high level of resources (computing power, storage space, energy). However, these are limited in end devices. The project team is developing methods to optimize AI models for use in resource-limited end devices.
Methods from machine learning for big data are to be applied to questions in atmospheric physics. Among other things, the representation of clouds in climate models and the predictability of weather situations will be worked on.