Research Groups

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Max Planck Institute for Intelligent Systems

Research focus: understanding, optimizing and predicting relations between the microscopic and macroscopic properties of complex large-scale interacting systems. I like to approach research by addressing application-oriented problems involving domain experts from different disciplines via developing models and algorithms derived from statistical physics principles.

Cyber Valley Research Fund Projects

  • Relaxing restrictive interdependence assumptions in networks

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Max Planck Institute for Intelligent Systems

Research focus: The group will focus on two areas. Firstly, on developing fabrication and integration methods of components made of various smart materials. Secondly, based on these newly developed fabrication methods, Wenqi Hu plans to investigate how to design bioinspired miniature soft machines, ranging from a few millimeters in size to tens of centimeters. The aim is to make such small untethered robots autonomous.

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Max Planck Institute for Intelligent Systems

Research focus: neuromechanics of locomotion, biorobotics, experimental validation with physical models, soft robotics, integrative systems biomechanics, systems biophysics, and biomaterials.

Cyber Valley Research Fund Projects

  • Soft-sensing interfaces with multifunctional smart materials

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University of Stuttgart

Research focus: Lee’s research group focuses on intelligent tactile systems and studies the sensing and perception mechanisms of biological systems. The group is part of the Institute of Smart Sensors (IIS) and develops artificial tactile systems that are then applied in contact-rich environments. In order to do so, the group is going to conduct interdisciplinary research at both the hardware and software levels, including research into new materials, sensor design, multiphysics simulation, sensor fabrication, signal processing, and machine learning. Their research has the potential to produce autonomous systems for contact-rich systems. These systems could, in perspective, be able to recognize contact as such and take advantage of their body’s surface for manipulation, motion planning, and nonverbal communication.

Lee’s research group is made possible by a grant from the Christian Bürkert Stiftung.

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Max Planck Institute for Intelligent Systems

Research focus: revolutionizing self-improvement and personal development, psychotherapy and psychiatry, brain training, and education by establishing a new science of improving the human mind and developing innovative approaches and technologies for empowering people to become more effective. Research thus focuses on understanding, promoting, and supporting cognitive growth, goal setting, and goal achievement.

Cyber Valley Research Fund Projects

  • A scalable machine leaning approach to improving human decision making
  • ACTrain: A personalised companion for enhancing executive functions based on adaptive meta-cognitive feedback

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Max Planck Institute for Intelligent Systems

Research focus: Developing algorithms to protect privacy when large data sets come to statistical conclusions on their own. Her goal is to solve challenging statistical problems in the field of machine learning and data protection.


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University of Stuttgart

Research focus: Developing new devices and microsystems for biomedical applications. The aim is to integrate actuation, recording, and calculation to advance medical procedures. Qiu is interested in developing tools that collect large amounts of data and learn from the data to understand the underlying principles. One research focus is to create realistic surgical robot testing and simulation environment based on rapid prototyping and augmented reality.

The Biomedical Systems research group receives funding from the Vector Foundation.

Cyber Valley Research Fund Projects

  • The Cyber-Physical Twin of Human Organs

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University of Tübingen

Research focus: Using machine learning methods to better understand important molecular processes in living cells, with a particular interest in epigenetic processes – e.g. what makes a liver cell or what blood cell what it if all cells in the body have the same genetic code? By working on the development of machine learning techniques for computer-aided gene identification, Schweikert wants to further advance the field of computational epigenomics, which shows great promise for medical applications.

The Computational Epigenomics research group receives funding from the Gips-Schüle Foundation.

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University of Göttingen

Research focus: developing intelligent systems that are as versatile as mammalian brains in terms of learning and performance. To this end, his group uses large amounts of neurophysiological and anatomical data to better understand the basics of neuronal intelligence and to reduce the gap between AI research and neuroscience. 

The Neuronal Intelligence research group receives funding from the Carl Zeiss Foundation.

Cyber Valley Research Fund Projects

  • Mechanisms of representation transfer

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Max Planck Institute for Intelligent Systems

Research focus: Developing autonomous intelligent systems that can learn and improve their perception and action skills through interaction with the environment. One main focus is learning-based approaches to image and sensor data analysis. Stückler develops methods with which robots can actively gain an understanding of their dynamic environment from sensor data and use it for complex tasks such as object handling or autonomous navigation. In addition to image data, he also uses other sensors such as tactile sensors for the artificial sense of touch when grasping or inertial sensors comparable to the human sense of balance.

Cyber Valley Research Fund Projects

  • Learning of physics-based models for visio-tactile object perception and manipulation
  • Self-supervised learning of mobility affordances for vision-based navigation

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RWTH Aachen University

Research focus: decision making, control, and learning for autonomous intelligent systems. Developing fundamental methods and algorithms that enable robots and other intelligent systems to interact with their environment through feedback, learn autonomously from data, and interconnect with each other to form collaborative networks. Turning mathematical and theoretical insight into enhanced autonomy and performance of real-world physical systems is an important and driving facet of the Intelligent Control Systems group’s work.

Cyber Valley Research Fund Projects

  • MachineData: Machine