Projects

AI4Nof1 combines clinical research with individual patient care to develop more personalized treatment recommendations. The project investigates adaptive N-of-1 studies, in which machine-learning methods learn from an individual patient's treatment course and improve recommendations over time.

Led by DFKI, the interdisciplinary competence network connects AI research with medical expertise. A particular focus is irritable bowel syndrome and the use of anonymized routine-care insights to bridge the gap between population-based evidence and individualized therapy.

KI4TUK develops an individualized, study-accompanying AI e-portfolio for the introductory phase of STEM degree programmes. The project aims to help students understand their strengths and learning needs, recommend suitable support and resources, and provide timely feedback in mathematics courses and laboratory work.

The project combines adaptive learning support and learning analytics with a techno-ethical perspective. Transparency, data autonomy and the responsible use of student data are treated as design requirements for a trustworthy learning assistant.

The Smart Data Innovation Lab is a collaboration and operating platform that brings together research, industry and the public sector to accelerate work with AI, Big Data and Smart Data technologies.

SDIL provides a secure data-room environment, high-performance GPU and cloud infrastructure, and a catalogue of Smart Data Innovation Services. Together, these resources support co-innovation on industrial data and help transfer advanced research methods into practical applications.

AI4EUROPE develops an open and collaborative AI research platform for the European research community. The platform connects researchers with data, services, tools and computing resources to support experimentation, knowledge sharing and the development of state-of-the-art AI systems.

The project also focuses on research productivity, reproducibility and collaboration between academia and industry.

There is a strong consensus that artificial intelligence will bring forth changes far more profound than any other technological revolution in human history. Depending on the course this revolution takes, AI will either empower our ability to make informed choices or reduce human autonomy; expand the human experience or replace it; create new forms of human activity or make existing jobs redundant.

Europe carries the responsibility of shaping the AI revolution. The choices we face today concern fundamental ethical issues about the impact of AI on labour, social interaction, healthcare, privacy, fairness and security. Making the right choices requires new solutions to fundamental scientific questions in AI and human-computer interaction.

Technical sensor systems offer capabilities superior to human perception: cameras capture more than visible light, high-speed cameras reveal invisible movement, directional microphones pick up distant sound. The vision of this project is to lay a foundation for digital technologies that provide novel sensory experiences and new perceptual capabilities that are natural and intuitive to use.

A particular focus is intuitive control mechanisms for amplified senses using eye gaze, muscle activity and brain signals — quantifying the effectiveness of new senses against the baseline of unaugmented perception, and demonstrating the feasibility of artificial reflexes.

SFB-TRR 161 is a collaborative, interdisciplinary research centre connecting 17 project teams from the University of Stuttgart, the University of Konstanz and the Max Planck Institute for Biological Cybernetics, working across four project areas in the field of visual computing.