Minds, Media, Machines
Mission

Minds, Media, Machines is an interdisciplinary network of researchers at the University of Bremen and of collaborators at national and international partner institutions. They are collaborating to advance our understanding of intelligence and cognition in autonomous agents and agent teams in the context of mediatized worlds. 

The aim of MMM is to advance research in high-profile areas such as artificial intelligence, robotics, machine learning, data science, social media, and mediatisation. This is done with a special emphasis on the benefit and welfare of the society, taking onboard aspects such as usability, privacy, security, sustainability, and lawfulness, and supporting different aspects of human life ranging from the education of children to support of the elderly. The insights gained within MMM are transferred into new generations of social, computer-based, and cyber-physical systems.

Collaborative research at the University of Bremen is focused on six interdisciplinary profile profiles, the High-Profile Areas. These contribute substantially to research at the University of Bremen and tie together the internal and external university research programs on campus. In the sense of a matrix structure, the High-Profile Areas lie across the scientific disciplines of the international departments. The internationally recognized top AI research in the state of Bremen is largely shaped by members of Minds, Media, Machines (MMM). They contribute their expertise and their potential to bring the Bremen AI strategy (see key issues paper) together with actors from the Bremen research landscape and regional companies.

© Patrick Pollmeier / Universität Bremen

Collaborative Research Center EASE:

Today, one of the core ingredients of Minds, Media, Machines is the interdisciplinary research center EASE that investigates everyday activity science and engineering at the University of Bremen. Its core purpose is to advance our understanding of how human-scale manipulation tasks can be mastered by robotic agents. To achieve this, EASE establishes the research area “Everyday Activity Science and Engineering” and creates a research community that conducts open research, open training, open data, and knowledge sharing. For further information, please visit the EASE-homepage.

The research findings are being transferred into a new generation of social, computer-based and cyber-physical systems that contribute substantially to the well-being of our society, such as cognitive assistance systems that accompany people throughout their lives and provide them with suitable support. In this context, people should decide for themselves on the use of their data.


Towards this aim, scientists in this High-Profile Area investigate human and machine knowledge representation, natural, formal and technical information processing, as well as secure transmission of information and computer-mediated communication.

The High-Profile Area is thus based on three pillars: Minds, Media, and Machines.

Minds

Performance of cognitive biological systems, including human cognition, is studied through empirical investigations, analyses and models. What are the building blocks of human cognition and cognitive capacities? How do we orient ourselves in space, and what can be learnt from and about the visual and auditory systems?

What are the roles of sensory-motor, and multimodal information processing, and how are experience and knowledge represented and processed? Further aspects investigated in this area are, i.a., planning of actions of varying degrees of complexity and abstraction, learning to manipulate simple objects, up to speech and  comprehension, as well as the study of interactions between a system, its environment, and communication between cognitive systems. Cognitive systems are always understood as being situated in a dynamic context that every investigation has to take into consideration. The knowledge and understanding gained on this basis is applied to develop formal methods and technical systems that aim to come as close as possible to the human case and human abilities.

For example, household robots that are, inspired by biology and cognitive science, able to learn from instructions designed by and for humans, including the ability to learn directly from observing human activities to the point that they can carry out the same tasks autonomously. 

Media

Today, individually as well as socially, we live in times of deep mediatization. In our everyday life, we interact with digital media and technical systems, whether we wish to or not. This omnipresent availability of technology constitutes both: new possibilities but also challenges, inter alia due to datafication and increasingly shorter innovation cycles. Media -and communication studies research the consequences of increasingly pervasive digital media and systems on individuals, society, and culture. Computer science is concerned with the processing and analysis of large quantities of data, with media informatics focusing on the design and development of new forms of interaction with digital media.  These subjects therefore build the foundation for data science as an emerging new research area. We study these topics, placing people and their needs at the center of our efforts.

Machines

The focus of research in this pillar is the development of intelligent technical systems that are able to meet a wide range of challenges. This includes the entire development chain, from the smallest hardware component to a fully functioning robotic system. The development of material-integrated sensorial systems, microelectronics, encoding of information and signal processing, the verification of circuits and systems, up to collaborative communication technologies, is studied here. The robotics research focuses on the development of autonomous systems that are developed for the use in specific scenarios, for example to operate in difficult locations such as the deep sea or Mars. In the area of ​​cyber-physical systems, we furthermore study the cooperation of intelligent networked systems.

The described three pillars Minds, Media and Machines do not stand separately from each other, they mutually support and enrich one another. Thus, cognitive science inspires robotics research to develop new robotic platforms. This in turn stimulates cognitive science to verify cognitive models through simulations. Finally, the analysis of mediatized worlds and the societal consequences of increasing penetration of technology into everyday life with digital media and processing systems of communication and media studies is again taken up in the cognitive sciences, that use these insights into communicative and social conditions for their research.

Minds, Media, Machines
History

The scientific focus Minds, Media, Machines is historically based in computer science. The thematic starting point was the interdisciplinary DFG-funded Collaborative Research Center SFB/TR 8 “Spatial Cognition”, in which spatial reasoning, spatial action, and spatial interaction of cognitive agents were researched from 2003 to 2014. After the end of its maximum funding period of twelve years, the interdisciplinary research center Bremen Spatial Cognition Center (BSCC) emerged from the SFB/TR 8 in 2015.

Facts & Figures

The MMM high profile area encompasses in total 33 professors and 429 researchers (March 2022). The majority of these researchers work in computer science (as of 2019: 26% women). The total third-party budget of MMM members at the university in 2020 and 2021 together amounted to about €46 million. In addition, members of MMM are responsible for a substantial number of further researchers working at collaborating external institutions.


0
Professors
0
Researchers

MMM-Office

The MMM Office is in charge of operational and organizational issues concerning MMM. In close coordination with the spokespersons, the Office supports activities within MMM  – from joint research initiatives, innovation processes, and MMM’s public relations, to initiatives for early career researchers and equal opportunities.

© Patrick Pollmeier / Universität Bremen
© Phaneendra Saya Boina

Dr. Dennis Küster
Science Manager

kuester@uni-bremen.de
Phone: +49 421 218-64266

Phaneendra Saya Boina
Innovation and Technology Transfer Manager

sayaboina@uni-bremen.de
Phone: +49 421 218-64288

Become a member now

Scientists employed at the University of Bremen who wish to become a member of MMM send a written application (by email) to the Spokesperson(s).