Project overview

What is the perfect place to live for the baby boomer generation? To clarify this question, mathematical methods and AI technologies are analyzed that can support decision-making processes in municipalities.

Prof. Dr. Marco Kuhrmann has been appointed as Endowed Professor for Agile Systems Development (with a focus on regulated domains) at Reutlingen University starting in the winter semester of 2021.

AI4ChemRisk analyzes the risks of chemical pollution from wastewater and agriculture in our freshwater ecosystems. AI models are used to predict contamination processes in order to improve their management.

The GENAI-X project conducts research on the generalisability of AI models under constantly changing environmental conditions. Its goal is to enhance the understanding and prediction of environmental phenomena.

How can artificial intelligence in microbiome research lead to better early detection of Alzheimer's disease or type 2 diabetes? Novel AI models are being researched that are designed to predict the microbiome composition in the event of physiological changes.

The use of AI methods is a key prerequisite for ensuring the competitiveness of medium-sized companies. The "AI Booster" doctoral college at Aalen University is therefore researching new AI models in order to better process and utilize data from manufacturing processes.

The AI project team at Mannheim University of Applied Sciences (THM) is researching the combination of bio-sensors with AI algorithms to reliably monitor the freshness of food in retail stores in real time.

In pharmaceutical research, the early detection of undesirable or even absent effects of therapeutics represents the greatest hurdle to successful To achieve a breakthrough in the treatment of brain tumors, an AI-based model for the interplay of gene activity and therapy response is being developed. The goal is to predict the effect of drugs and optimize personalized therapies for cancer patients.

75% of insect mass has been lost in the last 30 years. The BeeVision project team is therefore developing an AI system to monitor pollinator diversity by automatically recognizing the flight patterns of different insect groups.

The Federal Artificial Intelligence Competition encourages students with strengths in mathematics, computer science or physics to develop creative solutions for the challenges of the future. The foundation supports this project as the main sponsor.