Technical University of Munich (TUM) is one of Europe's leading research universities, with significant AI safety and reliable AI research programs including the Konrad Zuse School of Excellence in Reliable AI (relAI).
Technical University of Munich (TUM) is one of Europe's leading research universities, with significant AI safety and reliable AI research programs including the Konrad Zuse School of Excellence in Reliable AI (relAI).
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Updated 05/18/26Funding Details
Updated 05/18/26- Annual Budget
- $2,171,000,000
- Current Runway
- -
- Funding Goal
- -
- Funding Raised to Date
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Org Details
Updated 05/18/26The Technical University of Munich (Technische Universität München, TUM) was founded in 1868 by King Ludwig II as a polytechnic school and has grown into one of Europe's most prominent research universities. TUM has been designated a University of Excellence by the German federal government for four consecutive funding periods. The university is organized into seven schools covering computation and information technology, engineering and design, natural sciences, life sciences, medicine and health, management, and social sciences and technology, with its main campus in Munich and a large research campus in Garching. TUM's AI safety-relevant research is primarily organized through several major initiatives. The Konrad Zuse School of Excellence in Reliable AI (relAI), jointly operated with LMU Munich and funded by the German Academic Exchange Service (DAAD), is the flagship program for AI safety research at TUM. relAI focuses on making AI systems safe, secure, privacy-preserving, and responsible, with a research program that emphasizes formal guarantees and provable properties across four application domains: medicine and healthcare, robotics and interacting systems, algorithmic decision-making, and learning and instruction. The Munich Center for Machine Learning (MCML) is one of six federally-funded AI competence centers in Germany and brings together researchers from TUM and partner institutions. The Munich Data Science Institute (MDSI) serves as a cross-disciplinary hub for data science and AI research across the university. Individual researchers at TUM also contribute directly to AI safety. Leo Schwinn, a Lecturer at TUM in the Data Analytics and Machine Learning group under Prof. Stephan Günnemann, conducts research on adversarial robustness and vulnerabilities of large language models, including machine unlearning techniques and adversarial attack methods. TUM's AI safety work extends to policy and governance through the TUM Think Tank and collaborations with the Munich School of Philosophy on ethics and societal implications of AI development.
Theory of Change
Updated 05/18/26TUM pursues AI safety through a combination of foundational research and applied work aimed at producing AI systems with provable safety and reliability properties. The relAI school's theory of change centers on the idea that only formal, mathematically rigorous guarantees of AI behavior will generate the trust necessary for safe adoption in high-stakes domains. By training a new generation of AI researchers with deep technical grounding in safety, security, privacy, and responsibility, and by partnering with industry and policy institutions, TUM aims to ensure that AI technologies deployed in society meet rigorous reliability standards and that the broader research community has the tools and knowledge needed to build trustworthy AI.
Grants Received
Updated 05/18/26Projects– no linked projects
Updated 05/18/26Discussion
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