14.08.2026
Stephan Günnemann Featured in t3n on Data Poisoning and AI Security
Understanding the Growing Threat of Manipulated Data
MCML PI Stephan Günnemann is featured in a recent t3n article examining data poisoning as a growing threat to the security and reliability of AI systems. Data poisoning involves deliberately manipulating data to influence how AI models behave, potentially causing them to produce misleading or harmful results.
Günnemann highlights the broader implications of data poisoning, including its potential use to pursue political influence or economic advantages. The article explores how manipulated data can affect AI-powered systems such as recommendation services and why detecting such attacks remains a significant challenge.
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16.09.2026
Vincent Fortuin Receives ERC Starting Grant for Reliable Small-Data AI
MCML PI Vincent Fortuin receives an ERC Starting Grant for AutoBayes, advancing reliable AI methods for learning from small datasets.
