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Applied Machine Intelligence
Special Interest Group of the Doctoral Centre for Applied Computer Science (PZAI)
The Doctoral Centre for Applied Computer Science (PZAI) brings together more than 100 doctoral candidates from four Universities of Applied Sciences in Hesse, advancing interdisciplinary research at the forefront of applied computer science. Within the Special Interest Group (SIG) Applied Machine Intelligence, researchers investigate a broad spectrum of Artificial Intelligence topics — ranging from machine learning and computer vision to digital twins and robotics — with a strong focus on robust methods and real-world implementation.
Advancing AI Research to Solve Societal Challenges
At PZAI, we believe that AI can make a tangible difference in society. Our projects tackle complex challenges across conservation, healthcare, manufacturing, and beyond, combining research excellence with societal impact.
Examples of Applied Machine Intelligence Research in Action
Biodiversity and Conservation
Reliable data is the foundation for effective conservation strategies. One doctoral project focuses on understanding and protecting endangered species. Collaborating with research partners across Europe and Africa, the researcher applies computer vision methods to generate population estimates and develop tools to monitor animal populations. This approach allows ecologists to make informed decisions and implement targeted measures to counteract global biodiversity decline.
Industrial AI and Production Optimization
Smart Manufacturing
A doctoral candidate works with a global leader in industrial robotics to develop AI methods for early detection of faults in machines and manufacturing processes. The project addresses complex production environments, heterogeneous equipment, and limited computing power and data transmission rates. Close collaboration with the industry partner ensures that solutions are practical, scalable, and ready for real-world deployment.
Nonwoven Materials Production
Another project focuses on optimizing the production of nonwoven materials used in medical masks, automotive filters, and hygiene products. The researcher combines domain-specific expertise with informed machine learning, digital twins, and both simulated and real production data to model each stage of the manufacturing process in detail. The resulting insights enable manufacturers to improve product quality, reduce waste, and meet growing industry demand efficiently.
AI in Mental Health
Rising mental health challenges place increasing strain on healthcare systems worldwide. In collaboration with psychotherapists from several clinics, a doctoral researcher develops AI-based approaches to analyze therapy progress and provide actionable insights for both patients and therapists. This work supports more efficient, personalized care and helps alleviate the shortage of qualified mental health professionals.
Driving Impact Aligned with the United Nations SDGs
Research at PZAI addresses a wide range of societal, technological, and economic challenges that reflect the United Nations Sustainable Development Goals (SDGs), including Zero Hunger; Good Health and Well-Being; Quality Education; Gender Equality; Affordable and Clean Energy; Industry, Innovation, and Infrastructure; Reduced Inequalities; Sustainable Cities and Communities; and Climate Action. By combining extensive expertise in AI with application-oriented research, doctoral projects exemplify innovative research while creating measurable societal impact.