Chair for Machine Learning

The Chair for Machine Learning, led by Prof. Dr. Asja Fischer, has been established since 2019 and is part of the Faculty of Computer Science at the Ruhr University Bochum. It is associated with the Institut für Neuroinformatik (INI), the Horst Görtz Institute for IT Security (HGI), the Cluster of Excellence for Cyber Security (CASA), the Lamarr Institute and the European Laboratory for Learning and Intelligent Systems (ELLIS).

Our research is primarily focused on deep learning, with a core objective being the advancement of the foundations of deep learning. Despite the groundbreaking capabilities of modern deep neural networks, our theoretical understanding is still limited. However, we are convinced that a thorough theoretical understanding is needed for the trustworthy application of existing learning algorithms and the development of novel robust and efficient learning approaches. 

Another core area of our research is the intersection of machine learning and security. Here, we are interested in topics like uncertainty quantification, robustness against adversarial attacks, and defense strategies against the threats induced by artificial media generated by machine learning systems.