Our Mission Statement

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Our Vision

As a leading entrepreneurial university, we are a site of global knowledge exchange, shaping a sustainable future through talent, excellence and responsibility.

Our Mission

We inspire, promote and develop talents in all their diversity to become responsible, broad-minded individuals. We empower them to shape the progress of innovation for people, nature, and society with scientific excellence and technological expertise, with entrepreneurial courage and sensitivity to social and political issues, as well as a lifelong commitment to learning.

Our Core Values

Our core values form the foundation of our relationships with one another and with our cooperation partners:

  • Excellence: We cultivate an environment of curiosity, creativity and unconventional thinking across the disciplines and set the highest standards of performance in research, teaching, and innovation.
  • Entrepreneurial Mindset: We question the consequences of our actions, take on new challenges proactively, and continually enhance our working methods. We commit ourselves to socially reflected innovations and promote their commercial application by founding sustainable technology spin-offs.
  • Integrity: We draw our success from an inclusive community of talents from different backgrounds, cultures, ideas and perspectives. We act with respect for others and transparency in accordance with our shared values.
  • Collegiality: We respect and inspire one another in a vibrant culture of university community. We cultivate the academic, economic and social partnerships that make TUM a site of global knowledge exchange.
  • Sustainability and Resilience: We learn from our diverse experiences and see in persistent change the opportunity for the sustainable development of science, ecology, economy and society – from this we draw inspiration, motivation and resolve.

Our Guiding Principles

Governing Documents

An overview of central codes and regulations by which we shape research and innovation, teaching, and our governance as a top and modern university of international standing.

Governing Documents

Compliance

The TUM Compliance Office ensures the integrity and transparency of research, teaching and innovation based on the TUM Code of Conduct, the TUM Respect Guide, and the Statute on Safeguarding Good Academic Practice.

TUM Compliance Office

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News

Federally funded research center

Munich Center for Machine Learning launched

Machine learning and artificial intelligence are key technologies for the digital economy and society. Leibniz Prize winner Prof. Daniel Cremers from the Technical University of Munich (TUM) is one of the coordinators of a new competence center dedicated to these topics. The Munich Center for Machine Learning (MCML), which is funded by the Federal Ministry of Research, will in the future be connecting key areas of expertise from data science, computer science and statistics.

With advances in computing power, computers can intelligently link data and make predictions (Image: A. Heddergott).

With advances in computing power and new algorithms, computers can intelligently link data, pinpoint relationships, draw conclusions, and make predictions. This forms the basis for new diagnostic tools in medicine, or for self-controlling systems in logistics and industrial manufacturing.

In the Munich region, numerous outstanding researchers are conducting research in the field of Artificial Intelligence (AI).  In the current 2018 "Times Higher Education Ranking", the TUM occupies the sixth place in AI research worldwide. With the establishment of the Munich School of Robotics and Machine Intelligence (MSRM), which combines research on robotics and machine intelligence under one roof, TUM set new standards in 2017 for interdisciplinary research in this field. Director Prof. Sami Haddadin was awarded the Leibniz Prize in 2019 and Prof. Daniel Cremers was awarded the Leibniz Prize in 2016.

Consolidated expertise from data science, computer science and statistics

Daniel Cremers is an expert in deep-learning methods and neural networks in the field of computer vision and a co-coordinator of the newly established competence center, the Munich Center for Machine Learning (MCML). At the MCML, 15 teams from the fields of data science, computer science and statistics from LMU and TUM have come together to further advance the methods of machine learning and pattern recognition. The new facility is managed by Prof. Thomas Seidl (LMU).

From weather data to genome research

The new Competence Center is dedicated to the processing of various data types.  Weather data, stock prices, voice recordings or video sequences, for example, are all what is called a time series. Improving the deep-learning methods for such data series, advances the field of computer vision - an important component of autonomous driving. Social media, modern genome research and the diverse use of sensors today also produce enormous amounts of data, and the MCML teams are researching new methods to analyze this data. 

Research questions from real life

"The potential of new machine learning methods is huge and the range of socially relevant applications limitless," says Professor Daniel Cremers, head of the Chair for Computer Vision & Artificial Intelligence at the TUM.  The MCML also aims to put its research findings into practice, which is why companies are involved. 

Further information:

The MCML along with other competence centers for machine learning in Berlin, in the Rhine-Ruhr area and in Tübingen will be funded for four years by the Federal Ministry of Education and Research (BMBF). These centers will receive a total of 7.5 million euros. The promoter of the BMBF initiative is the German Aerospace Center (DLR). 

Contact:

Prof. Dr. Daniel Cremers
Technichal University of Munich
Chair Computer Vision and Artificial Intelligence
Tel.: +49 (89) 289 - 17755
cremers@tum.de

Technical University of Munich

Corporate Communications Center

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