Prof. Dr. Eirini Ntoutsi

I am a Full Professor of Robust and Responsible Artificial Intelligence at the Faculty of Computer Science, University of the Bundeswehr Munich (UniBwM), and a member of the Research Institute CODE for cyber defence and smart data. My research focuses on developing AI systems that remain robust, responsible, and adaptive under real-world conditions. I study how learning systems respond to distribution shifts, data imbalance, bias, adversarial manipulation, and evolving environments, and develop methods for fairness, robustness, explainability, and reliable adaptation. A central theme of my work is understanding the capabilities, limitations, and societal implications of AI systems, including modern foundation and generative models. My broader vision is to create AI systems that remain reliable and responsible throughout their lifecycle, augment human capabilities, and benefit society. Previously, I was a Full Professor of Artificial Intelligence at the Department of Mathematics and Computer Science, Freie Universität Berlin (FUB) and an Associate Professor of Intelligent Systems at the Faculty of Electrical Engineering and Computer Science, Leibniz University Hannover (LUH). I remain a member of the L3S Research Center. Prior to joining Leibniz University Hannover, I was a postdoctoral researcher at Ludwig-Maximilians-Universität München (LMU), in the group of H.-P. Kriegel, which I joined in 2010 as an Alexander von Humboldt Fellow . I received my Ph.D. from the University of Piraeus (UniPi), Athens under the supervision of Y. Theodoridis and hold an M.Sc. and Diploma in Computer Engineering and Informatics from the University of Patras (UPatras), Greece.

Research Areas

• Robust & Reliable AI (Distribution shifts, Data imbalance, Adversarial robustness, Reliability and evaluation, ...)
• Responsible AI (Bias and Fairness, Explainability, Accountability, AI safety and security, ...)
• Adaptive AI (Data streams, Online learning, ...)
• Generative & Data-centric AI (Foundation models, Data augmentation, Synthetic data, Data quality and bias transfer, ...)

Teaching

I teach and supervise students in Artificial Intelligence, Machine Learning, Data Mining, Adaptive AI, and Responsible AI. My approach to teaching and supervision is inspired by Nikos Kazantzakis, who beautifully describes the role of a mentor and educator:

“Ideal teachers are those who use themselves as bridges over which they invite their students to cross, then having facilitated their crossing, joyfully collapse, encouraging them to create bridges of their own.”

Selected Recent Talks

• IEEE ICDM 2026, Blue Sky Forum, Shenyang, China, "Explaining Changes in Evolving Systems"
• IEEE ICDM 2026, Incremental Learning Workshop, Invited talk: "Responsible AI under Change"
• European Conference on Algorithmic Fairness (ECAF) in Ghent, Belgium - Keynote: Tensions and Trade-Offs of Algorithmic Fairness - From Metric Incompatibility to Cross-Pillar Trade-Offs (slides).

Professional Activities & Affiliations

My academic activities include research leadership, community service, conference and workshop organization, reviewing and editorial activities, and participation in national and international AI initiatives.

Member of ACM · IEEE · AAAI · IASEAI · ELLIS Society · Gesellschaft für Informatik (GI) · Hellenic Artificial Intelligence Society (EETN)