The research group Data Mining and Machine Learning investigates novel approaches to exploratory data analysis, unsupervised, semi-supervised and supervised learning. We focus on methods for various data types including texts, graphs, high-dimensional feature vectors and other complex structures. We consider different tasks, e.g., representation learning, embedding, clustering, causality detection, classification and reinforcement learning.

The research group Data Mining and Machine Learning consists of four work groups:

Our methods are inspired by challenges arising from different application areas, e.g. medicine, neuroscience, pharmacoinformatics, renewable energies and social sciences.

Team of research group DM

Publications of research group DM

Projects of research group DM


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Review of the Kaiserschild Lectures with Prof. Claudia Plant "AI in Medicine" [german]

On 15 April, experts discussed the question of whether artificial intelligence can revolutionise medicine as part of the Kaiserschild Lectures series. Among the panelists:...

Two papers accepted at KDD 2021

We are happy to announce that two papers have been accepted at KDD (acceptance rate 15%)

Paper accepted at IJCAI 2021

Our paper "Details (Don't) Matter: Isolating Cluster Information in Deep Embedded Spaces" has been accepted for presentation at IJCAI-21 (13.9% acceptance rate).

Wir freuen uns Benjamin Roth an unserer Fakultät willkommen zu heißen. Die neugeschaffene Professur "Digitale Textwissenschaften" ist an der Fakultät für Informatik und der...

On 1.5.2020, Dr. Nils Morten Kriege joined our faculty on a tenure track professor-position with his interdisciplinary Data Science project "Algorithmic Data Science for...

Job offer at Data Mining

We are hiring. We are searching for a PhD student with strong interest in data mining.

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