The chair studies data mining techniques and knowledge discovery approaches that are at the core of data science. The group is known for its contributions to the areas of predictive analytics, automation of machine learning and networked science, subgroup discovery and exceptional model mining, and similarity computations on complex data. Its research is inspired by theoretical computer science, systems development and real-world applications of (big) data-driven discovery. The group is actively collaborating with scientists from academia and industry at both national and international levels.
Information for CSE, BIS, ES and other TU/e master students willing to do their graduation projects with us can be found here.
We will be adding more relevant information shortly.