Munich Center for Machine Learning (MCML)


Prof. Dr. Bernd Bischl, Chair of Statistical Learning & Data Science (LMU)

Prof. Dr. Daniel Cremers, Chair of Image Processing and Artificial Intelligence (TUM)

Prof. Dr. Thomas Seidl, Chair of Database Systems and Data Mining, and MCML spokesperson (LMU)

Prof. Dr. Daniel Rückert, Chair of Artificial Intelligence in Healthcare and Medicine (TUM)

The Munich Center for Machine Learning (MCML) is a joint initiative of leading researchers from the Ludwig-Maximilians-Universität München and the Technische Universität München. The MCML is institutionally funded with almost 20 million Euros annually by the Federal Ministry of Education and Research (BMBF) and the Free State of Bavaria. The aim of the center is to advance basic research in the field of artificial intelligence (AI) and machine learning (ML).

The mission of the MCML is to bring together leading researchers in Germany, strengthen regional, national and international expertise in the field of AI and make the corresponding potential available to users from science and industry.

The MCML is actively establishing collaborations with other universities and research institutions as well as industry. The MCML now consists of international research teams of around 60 professors with over 250 researchers. Almost a third of the professors are involved in the newly established AI professorships of the Hightech-Agenda Bavaria.

The research focus at the MCML is divided into three areas: In the “Foundations of Machine Learning” area, the computer science, statistical and mathematical foundations of ML are explored in depth and the explainability of AI. It forms the basis for methodological advances in ML.
The research focus “Perception, Vision and Natural Language Processing” deals with how computers can extract and process information from images and natural language -key technologies for a variety of practical applications.
The research focus “Domain- specific Machine Learning” combines expertise from the fields of medicine, biology, physics, geosciences as well as social and human sciences. AI methods for application-related and socially relevant problems are developed in close cooperation with the other two areas.

Other important components of the MCML are its service, transfer and training offers. In addition to training students, the MCML offers a dedicated junior researcher program for young scientists. This includes a doctoral program, a large number of postdoctoral positions, dedicated junior research groups and the newly established Thomas-Bayes-Professorship program.