• 07.26.2022
  • Reading time 5 min.

TUM and LMU's Munich Center for Machine Learning to receive permanent funding

Big coup for AI research in Munich

The Munich Center for Machine Learning (MCML) will receive permanent funding from the German government and the state of Bavaria. MCML, a joint initiative by the Technical University of Munich (TUM), and Ludwig-Maximilians-Universität München (LMU), is one of six AI centers of excellence throughout Germany. As a result, regional research into artificial intelligence (AI) and particularly machine learning will gain considerable cachet within the knowledge hub of Munich and beyond.

The Frauenkirche in Munich Jan Antonin Kolar / Unsplash
TUM and LMU's Munich Center for Machine Learning (MCML) will receive long-term funding from the German federal government and the Free State of Bavaria. The MCML is one of six AI centers of excellence nationwide and is intended to make the Munich region even more attractive for young talent.

MCML is a joint undertaking by TUM and LMU. Its goal is to further advance basic research in the field of AI, with a strong focus on practical applications. MCML was founded in 2018 as one of six AI centers of excellence throughout Germany and has been funded since then by the German Federal Ministry of Education and Research (BMBF). It now consists of more than 50  research groups both in basic research and in the domain of application-oriented machine learning. For the centers now definitively established after their successful evaluation, BMBF and the respective state governments will jointly provide up to 100 million euros annually in total. MCML is set to receive 19.6 million euros every year.

“Great teamwork between TUM and LMU“

“The AI centers of excellence are a mainstay of AI research in Germany. By consolidating their funding, we are giving the researchers planning certainty and the ability to embark on longer-term and more complex investigations when opportune. We also expect the decision to deliver fresh stimuli to the centers – especially as regards knowledge transfer, the founding of AI start-ups, and international connectivity. After all, we will only retain our technological sovereignty in AI if we bring our research results to application more quickly and cultivate sovereignty at the European level. I am convinced that the Munich AI center of excellence, with its strengths in machine learning, in spin-offs, and in key fields of application such as medicine and the humanities and social sciences, will play a major role in the achievement of this goal,” says Mario Brandenburg, Parliamentary State Secretary at BMBF.

“The digital revolution is moving into the next phase. Machine learning is playing an increasingly prominent role – including in application: industry, mobility, the care sector. In MCML, we are pooling the AI expertise of our two universities of excellence. This is great teamwork between TUM and LMU,” says Markus Blume, Bavarian State Minister of Science and the Arts.

“Pooling our strengths to drive forward the development of AI”

“The decision by federal and state governments to make MCML a permanently funded center of excellence is a clear marker of the success of our One Munich strategy  By pooling our strengths, we want to drive forward future development in the domain of artificial intelligence. This will make Munich an even stronger magnet for young talent,” says Prof. Thomas F. Hofmann, President of TUM.

“MCML offers a very attractive scientific environment with first-class cooperation opportunities,” says LMU President Professor Bernd Huber. “Obtaining the permanent funding from federal and state governments is a big coup and at the same time a sign of the outstanding quality of MCML. For participating scientists at the Munich location, it offers them the opportunity to further advance their machine learning research projects.“

Three focus topics

The focus of research at MCML is divided into three areas: The scientists at the center want to deepen the computational, statistical, and mathematical foundations of machine learning and research the explainability of AI – that is to say, among other things, how algorithms learn automatically with the help of vast amounts of training data and arrive at decisions. A second focus area is “Perception, Vision, and Natural Language Processing” – in other words, how computers can extract and process information from images and natural language – key technologies for a variety of practical applications. And finally, the third focus area is the development of machine learning methods for various socially relevant application fields – in the domains of medicine, biology, physics, geosciences, and the social sciences and humanities. In addition, MCML offers transfer and training services as well as other kinds of services. To this end, it collaborates with other scientific institutions and companies. On top of this, it educates and trains students.

“By virtue of the close connection between basic and applied research, MCML helps new machine learning approaches reach the general public much more quickly,” says Prof. Daniel Cremers, spokesperson of MCML and Chair of Computer Vision and Artificial Intelligence at TUM. “Through the cooperation of top-class researchers at MCML, we want to make Munich an even more attractive location for young talent from the field of machine learning,” says Laura Leal-Taixé, MCML spokesperson and Professor for Dynamic Vision and Learning at TUM. “With our research activities at MCML, we’re creating new methodological foundations for the advancement and application of data science, data mining, machine learning, and artificial intelligence,” says Professor Thomas Seidl, Chair of Database Systems and Data Mining at LMU and spokesperson of MCML. “Attracting and retaining the best and brightest minds is one of our top priorities at MCML. “Attracting and retaining the best and brightest minds is one of our top priorities at MCML. By offering attractive, independent research positions for young scientists, we are preparing them for a hopefully long-lasting and very successful career in academia“, says MCML spokesperson Prof. Bernd Bischl, Chair of Statistical Learning and Data Science at LMU.

Further information and links

Technical University of Munich

Corporate Communications Center

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