Data Mining and AI

Profile

The Data Mining and AI Group, headed by Prof. Thomas Seidl, researches current methods at the intersection of data mining, machine learning, database systems, and artificial intelligence. Their research focuses on key topics such as clustering, active learning and learning with limited labels, process mining, and multimodal as well as visual-language learning. As part of the Munich Center for Machine Learning (MCML), they combine foundational research with practical applications in various domains.

Current research topics

• Process mining
• Unsupervised learning
  • Clustering
  • Subspace clustering
  • Deep clustering

• Semi-supervised learning
  • Active learning
  • Few labels Learning

• Large vision-language learning

• Outlier detection
• Stream mining

Publications