MMM-Fair, the open-source toolkit for fairness analysis in AI systems, was recently featured in the German tech magazine IT Boltwise.
The Artificial Intelligence and Machine Learning (AIML) group, led by Prof. Dr. Eirini Ntoutsi, researches and develops AI systems that aretechnically robust, resilient to biases, data imbalances, distribution shifts, adversarial attacks, and other real-world challenges, andsocietally responsible, with emphasis on fairness, explainability, and accountability.
Three fundamental questions drive our work:How can we build intelligent machines for the real world? Equally important,what kind of intelligence do we aspire to build? And,can AI exhibit creativity?
Our ongoing research includes:
- Continuous learning over evolving data and data streams
- Responsible AI with a focus on fairness-aware machine learning, explainable AI and (adversarial) robustness
- Generative AI for enhancing data quality for AI and enabling novel solutions
Our applications span diverse domains, including education, agriculture, banking, and engineering.
We apply our methods across various sectors, including education, social networks, banking, agriculture, manufacturing, and engineering. Our group is part of the research institute CODE for Cybersecurity and Smart Data and theDepartment of Computer Science at theUniversität der Bundeswehr München (UniBwM).Previously, we worked at the Freien Universität Berlin andLeibniz Universität Hannover/ L3S Research Center.
