Uniting leading researchers in Germany, to strengthen regional, national and international competence in the field of machine learning and making corresponding potential accessible to users from science and industry

The Munich Center for Machine Learning

In recent years, Machine Learning (ML) and Artificial Intelligence (AI) have become essential key technologies in all areas of our lives. The world would benefit massively from these new technologies. However, the migration of technologies from science to practice still remains a tough challenge.

The Munich Center for Machine Learning (MCML) is made up of leading researchers from the Ludwig-Maximilians-University Munich (LMU Munich) and the Technical University Munich (TU Munich). They are experts in the fields of data science, computer science and statistics.

Pursuing the goal of strenghtening regional, national and international competence in the field of machine learning, MCML’s fundamental research is bundled in five competence areas:

In order to transfer new concepts of the field of machine learning to application areas, the MCML focuses on practical research and works closely with

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MCML Team

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Prof. Dr. Thomas Seidl

is a professor for Computer Science and head of the Database Systems and Data Mining Group at LMU Munich. His fundamental research on data mining and database technologies with application domains in engineering, business, life science and humanities yielded more than 300 scientific publications so far. He serves on many program committees and scientific boards and is co-chair of the LMU Data Science Lab, the ZD.B Innovation Lab, the Munich School of Data Science @ Helmholtz, TUM & LMU (MuDS) and of the elite Master program in Data Science at LMU.

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Prof. Dr. Bernd Bischl

is a professor for Computational Statistics at LMU Munich since 2015 and head of the Münchener R-Kurse. His research interests are data science, machine learning, model selection, model-based optimization, statistical software and parallel computing. Prof. Bischl is also a member of the steering committee of the Data Science Certificate Program of the LMU, where he teaches Machine Learning and Deep Learning.

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Prof. Dr. Daniel Cremers

holds the chair for Computer Vision and Artificial Intelligence at TU Munich since 2009. In 2002 he obtained a PhD in Computer Science from the University of Mannheim, Germany. Subsequently he spent two years as a postdoctoral researcher at the University of California, Los Angeles (UCLA) and one year as a permanent researcher at Siemens Corporate Research in Princeton, NJ. From 2005 until 2009 he was associate professor at the University of Bonn, Germany. In 2016, Prof. Cremers received the Gottfried Wilhelm Leibniz Award, the biggest award in German academia.

Research Areas

Spatial and Temporal Machine Learning

Spatial and spatio-temporal data, i.e. data with a dynamic spatial or time component such as sensor data or camera recordings, play an important role [...]

Learning on Graphs and Networks

In many data-intensive applications, from social media, genome research to mobility, attributed graphs and networks have proven to [...]

Representation Learning

The research field of representation learning involves the automated generation of meaningful features from high-dimensional data sets [...]

Model Selection, Validation and Explainable ML

Valid benchmarking of machine learning methods is essential to gain robust guarantees for the practical use of models [...]

Computational Models for Large-Scale Machine Learning

The area of competence “computational models for large-scale machine learning” focuses on several topics in the field of unsupervised machine learning [...]

Partner

The MCML is working on cutting-edge research projects in different areas of machine learning

Services and Staff

The MCML integrates several services, intended for collaboration and outreach to other research insitutions, industy and startups.

General Manager

mailto:contact@mcml.ai

The general manager coordinates all activities within MCML and maintains relationships with partners outside the center.

Industry Collaborations

mailto:contact@mcml.ai

The MCML is actively looking for collaborations at the intersections of research and industry. For additional information, contact us!

Open Source and Open Data

mailto:michel.lang@stat.uni-muenchen.de

We want to actively contribute to the world of open source and open data. This means that we aim to share results of our research in an open source form.

Practical trainings for students

mailto:contact@mcml.ai

The MCML offers in-depth practical trainings for students based on real industry or research questions and usecases.

Statistical consulting

https://www.stablab.stat.uni-muenchen.de/index.html

The statistical consulting unit at LMU will integrate a wide variety of machine learning techniques into its portfolio.

Professional Training Courses

mailto:giuseppe.casalicchio@stat.uni-muenchen.de

Machine Learning and programing skills are widely required in the digital era. We want to enable industry and research partners with those skills in order to [...]

Entrepreneurship-Training

mailto:contact@mcml.ai

We collaborate with the LMU Entrepreneurship Center to actively give our members and partners the opportunity to create a bussiness out of research findings or their own ideas.

Research Coordinator TUM

mailto:contact@mcml.ai

We aim to bring recent research advances from the field of machine learning into other domains by teaching universty students.

Contact

Get in touch with us!

mailto:contact@mcml.ai

Are you interested in working with us, either as a researcher or in form of an industry or research cooperation? Do you see valuable use-cases for Machine Learning in your company? Are you a journalist reporting on the future of Machine Learning and Artificial Intelligence We look forward to hear from you via e-mail.

Munich Center for Machine Learning


Ludwig-Maximilians-University Munich

Institut für Informatik

Oettingenstr. 67

80538 München

Germany

Web

Ludwig-Maximilians-University Munich

Institut für Statistik

Ludwigstr. 33

80539 München

Germany

Web

Technical University Munich

Department for Computer Science / Informatik 9

Boltzmannstr. 3

85748 Garching

Germany

Web