TUM Innovation Networks

With the cross-disciplinary TUM Innovation Networks as part of our excellence strategy TUM AGENDA 2030, we aim to achieve several goals at once: On the one hand, the Innovation Networks are intended to promote the pioneering spirit of our scientists in new fields. After all, curiosity is one of the most important drivers for producing scientific and technological innovations.

Secondly, we want to address high-potential topics that can only be successfully addressed through interdisciplinary research approaches. That is why we exclusively support collaborations of researchers from different disciplines and departments in order to strengthen the bridges between them and to intensively investigate transdisciplinary areas for several years.

Thirdly, we want to identify and take up promising and high-potential research foci at an early stage for TUM, in order to later pave the way for elaborate and extensive research proposals in Germany or at EU level.

As TUM, we are also consciously taking a risk. This means that we knowingly accept that projects can also fail, but at the same time create the conditions for truly groundbreaking innovations. The TUM-IAS as a knowledge exchange center with its experienced and proven evaluation system at the highest international level is exactly the right place to hold the competition for the best ideas and then to permanently accompany the Innovation Networks and evaluate them later.

Transdisciplinary teams, collective creativity, new ideas

In the first round between July and September 2020, a total of 32 teams from TUM submitted project proposals. A specially established Innovation Network Board deliberated on these proposals in October. Its members included Prof. Gerhard Kramer as Senior Vice President Research and Innovation, Prof. Barbara Wohlmuth as Director of TUM's International Graduate School of Science and Engineering (IGSSE), and Prof. Michael Molls as Director of TUM-IAS.

12 days of intensive science – TUM-IAS as a fairground of knowledge

In an elaborate process, the Innovation Network Board selected various groups, which then had the opportunity to further condense and refine their proposals by Christmas 2020. The main element of this was the total of six two-day Exploratory Workshops in November and December, which were prepared and conducted in close cooperation with the TUM-IAS team. Each group presented and discussed different questions and aspects of the proposal and was expertly accompanied in this process by mentors. Such mentors were found, for example, among the TUM-IAS Fellows or the TUM Distinguished Affiliated Professors.

The first successful round – 3 Innovation Networks

In January 2021, the Innovation Network Board had to make a selection from the six highly complex and transdisciplinary proposals that had been elaborated and shaped during the Exploratory Workshops and had been reviewed by TUM external scientists. The TUM university management had the final say in this, and the selected three successful projects are already underway. They deal with

  • Neurotechnology for Mental Health (NEUROTECH), Prof. Simon Jacob, Medicine
  • Artificial Intelligence powered Multifunctional Material Design (ARTEMIS), Prof. Alessio Gagliardi, Electrical Engineering
  • Robot Intelligence in the Synthesis of Life (RISE), Prof. Job Boekhoven, Chemistry, Friedrich Simmel, Physics

Neurotechnology for Mental Health (NEUROTECH)

Disorders of mental health are amongst the most pressing medical problems that our society faces. Phenomena such as cognitive deficits, depression or chronic pain are caused by disorders of the brain and nervous system, but the mechanisms remain unclear. The TUM Innovation Network for Neurotechnology in Mental Health (NEUROTECH) develops new approaches and technologies to improve the precision of clinical diagnoses and the success of treatments for mental dysfunction.

The team uses electrophysiological methods to record and modulate brain activity at an extraordinary level of detail and combines them with cutting-edge tools from data science. The aim is not only to better understand and differentiate mental disorders, but also to create new, individualized technology based treatment modalities for patients. The researchers are following strict ethical guidelines in all steps of their work and also investigate the ethical implications of disruptive technological innovations in mental health for the individual and entire societies.

Artificial Intelligence powered Multifunctional Material Design (ARTEMIS)

Creating sustainable energy storage solutions and at the same time producing novel materials for regenerative medicine: Both is possible when using the right supramolecular chemical compounds. The TUM Innovation Network for Artificial Intelligence powered Multifunctional Material Design (ARTEMIS) is aiming at the guided discovery of such molecules and at developing them as a unique toolbox for different applications, using Machine Learning and Additive Manufacturing. Potential applications range from electrocatalysis for hydrogen production to guided tissue regeneration and ‘smart’ coating of medical implants. Data-driven prediction represents a novel and powerful way to boost the discovery, synthesis and the design of new multi-functional materials, as well as for scaling-up and fabrication of devices.

Robot Intelligence in the Synthesis of Life (RISE)

How did life emerge? Could it exist elsewhere? Could we even synthesize life – a system that is self-sustaining, self-replicating and evolving? The TUM Innovation Network for Robot Intelligence in the Synthesis of Life (RISE) aims to develop a radically new approach to these centuries-old questions, combining machine learning and robotics with chemical and biophysical experiments.

Robots will not only take tedious tasks out of the scientists’ hands, but actually become part of the experiments. By allowing the robots to observe data in real-time, let them analyze experiments, and, via artificial intelligence, change the course of the experiments, the scientists anticipate that a self-learning experiment evolves towards a system that displays the essential hallmarks of life. It is a development with the potential to revolutionize research and development in both industry and academia.


Over the next four years, seven to ten Principal Investigators (PIs) will work closely together across disciplines in each Innovation Network. The teams will further consist of up to ten PhD students and postdocs in addition to the PIs. The total volume of each project is approximately 3 million euros. The next round of calls for proposals will begin in 2021.