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.

Latest News

Paper Accepted at AAAI’25

Our PhD Student Amr Abourayya under the supervision of Michael  Kamp (IKIM) successfully published his paper entitled „Little is Enough: Boosting Privacy by Sharing Only Hard Labels in Federated Semi-Supervised Learning“ at the top-tier AAAI 2025 Conference

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TRR Kick-Off

New Research Project! From 21.11 to 22.11 all principal investigators and research assistants met in Lüdenscheid (NRW) to kick off the newly DFG-funded collaborative research center (or TRR in short)

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Contact

Anja Brüll, M.A.

E-mail: anja.bruell(at)rub.de

Phone: (+49) (0) 234 / 32-22797

Postal Address

Ruhr University Bochum
Faculty of Computer Science
Chair for Machine Learning
Universitätsstraße 150
44801 Bochum

Directions

The Chair for Machine Learning is located in building MC, starting with room 5.123. Directions can be found here.