Network Role: Partner

  • Another milestone for AI from the Stuttgart region

    Another milestone for AI from the Stuttgart region

    The future of Artificial Intelligence (AI) is taking an important step forward in the heart of Baden-Württemberg: the High-Performance Computing Center Stuttgart (HLRS) is joining the ‘KI-D@ARENA2036-X” program as a new partner, contributing its expertise and computing capacity. 

    The program is jointly driven by ARENA2036, Cyber Valley GmbH, DeepScenario, waveye, and the Technical Information and Communication Services of the University of Stuttgart (TIK).

    With HLRS joining the initiative, the program gains an important new partner. This collaboration provides access to the infrastructure project HammerHAI. Starting in mid-year, extensive AI computing resources will be available across the entire development chain—from smaller systems directly integrated into machines or devices to powerful high-performance computing systems. This will make it possible to train and deploy very large and complex AI models.

    Infrastructure designed to accelerate AI development

    As part of the initiative, the partners are building an open IT and data infrastructure, including access to a data space for the sovereign exchange of data. The goal is to provide companies with easy access to powerful resources for AI applications—from the initial idea to practical deployment within companies. At the center of this effort is the networking of AI systems and data. Companies will be able to use the provided infrastructure without having to build large technical systems themselves. Access will be offered at competitive costs. Start-ups as well as small and medium-sized enterprises (SMEs) will particularly benefit, strengthening their innovative capacity and competitiveness.

    This will create a scalable, transparent, and collaboratively designed system in Baden-Württemberg. Instead of a black-box approach, the project deliberately focuses on an open infrastructure.

    This infrastructure is built on three key components:

    Integrating own hardware

    Companies can integrate their own computing hardware, allowing them to flexibly expand available computing capacity and address individual requirements.

    Shared data space

    A scalable, collaborative data space with marketplaces enables different organizations to work together on datasets, AI models, and concrete use cases.

    High-performance computing with HammerHAI

    Powerful high-performance computing resources enable the training and deployment of particularly large AI models.

     

    A program that accelerates companies

    Participating companies in the ‘KI-D@ARENA2036-X’ program benefit from practical access to powerful AI infrastructure and a strong innovation network.

    The program offers, among other things:

    • the opportunity to test and implement new ideas and proof-of-concepts without high upfront investments
    • access to powerful high-performance IT without having to operate their own data center
    • professional exchange with other AI developers facing similar technological challenges
    • a real-world testing environment at ARENA2036 that brings together requirements from different industries

    This means the program not only supports companies in their projects—it actively accelerates the development and implementation of new AI applications.

    Voices from the project team

    Prof. Dr. Peter Middendorf, Rector of the University of Stuttgart:

    “The IT and data infrastructure of ‘KI-D@ARENA2036-X’ is another important building block in our innovation ecosystem. The University of Stuttgart contributes to the success of this project through its Technical Information and Communication Services and as a partner of ARENA2036. I am therefore particularly pleased that the High-Performance Computing Center Stuttgart (HLRS) is now joining as another strong partner. With its powerful computing infrastructure, HLRS will support companies and start-ups in testing and optimizing state-of-the-art AI applications.”

    Dr. Alexander Lahl, Regional Director of the Verband Region Stuttgart:

    “Together with the HammerHAI infrastructure project, an important nucleus for AI development is emerging in the region. Start-ups and especially small and medium-sized enterprises will benefit greatly from this initiative. Through our support, we are significantly strengthening the Stuttgart Region as a location for AI applications and data infrastructures. At the same time, this project highlights the importance of collaboration across research, industry, and regional partners.”

    Michael Kaiser, Managing Director of Wirtschaftsförderung Region Stuttgart GmbH (WRS):

    “The collaboration between ‘KI-D@ARENA2036-X’ and HLRS and its European AI Factory HammerHAI is another important building block for the AI ecosystem of the Stuttgart Region. It enables companies to train and use very large AI models using efficient high-performance computers—without having to operate their own data center. This opens up new opportunities in AI development and application, especially for small and medium-sized companies.”

    Angelina Jukic, Program Manager at Cyber Valley GmbH:

    “Our goal within the KI-D@ARENA2036-X program is to create a highly connected ecosystem that brings together research, start-ups, and industry. This will make the development and training of AI models more efficient. HammerHAI is one of Germany’s leading AI computing infrastructures and works together with ARENA2036 on forward-looking solutions.”

     

    Project status and outlook

    Following the successful establishment of the basic infrastructure during the first year of the project, the program will enable operational access to the available computing and data resources in 2026.

    About the KI-D@ARENA2036-X program

    The KI-D@ARENA2036-X program is jointly implemented by ARENA2036, Cyber Valley GmbH, DeepScenario, waveye, and the Technical Information and Communication Services (TIK) of the University of Stuttgart. The goal is to build a collaborative infrastructure that accelerates AI innovation in Baden-Württemberg while ensuring security, transparency, and long-term economic sustainability.

    The program is funded by the Verband Region Stuttgart within the Co-Financing Program for Artificial Intelligence from 2024 to 2027 with a total of €685,000.

    Presscontact:

    Silke Dutz

    Public Outreach Manager      

    Email: silke.dutz@cyber-valley.de   

  • Pierre Schumacher receives RIG “Outstanding Doctoral Thesis Award” at the German Robotics Conference 2026

    Pierre Schumacher receives RIG “Outstanding Doctoral Thesis Award” at the German Robotics Conference 2026

    Pierre Schumacher has been selected as one of the two recipients of the “RIG Outstanding Doctoral Thesis Award”, recognizing exceptional doctoral research in robotics in Germany. The award was officially announced during the “RIG Heroes Award Night 2026” at the German Robotics Conference 2026, organized by the Robotics Institute Germany (RIG), in Cologne on March 12.

    Schumacher’s dissertation, “Reinforcement Learning for Muscle-Driven Systems,” was selected from 27 nominations submitted by 16 institutions across Germany. Following an extensive evaluation process, an international selection committee chose two equal awardees, citing Schumacher’s work for its “scientific depth, originality, and impact”.

    Pierre Schumacher conducted his doctoral research at the Max Planck Institute for Intelligent Systems in Tübingen under the supervision of Prof. Georg Martius (University of Tübingen) and Prof. Daniel Häufle (Hertie Institute for Clinical Brain Research) funded by the Cyber Valley Research grant “Learning effcient control of non-linear muscle-driven systems: Morphological computation as guiding principle”. His project was part of the Cluster of Excellence “Machine Learning: New Perspectives for Science” and the Center for Bionic Intelligence Tübingen Stuttgart (BITS). His dissertation, “Reinforcement Learning for Muscle-Driven Systems,” addresses challenges in controlling complex, highly overactuated robotic and biomechanical systems by developing new machine learning methods.

    A central contribution of the work is the development of DEP-RL, a reinforcement learning approach that improves exploration and learning in systems with many redundant actuators, such as musculoskeletal models. Using this method, Schumacher demonstrated efficient learning for tasks involving complex simulated bodies, including a human model with dozens of muscles and animal-inspired locomotion systems.

    Pierre’s research also explored how muscle-like actuation can improve learning performance and robustness in robotic systems. In collaborative studies, Schumacher and colleagues showed that musculoskeletal models can lead to more data-efficient and stable learning in anthropomorphic control tasks. More recent work demonstrated that reinforcement learning can produce natural and robust bipedal walking in musculoskeletal simulations without relying on motion-capture demonstrations.

    Schumacher began his academic path with a trinational bachelor’s degree in physics that took him to universities in France, Luxembourg, and Germany. After completing his B.Sc. in physics in Saarbrücken 2017, he shifted toward computational approaches and pursued a master’s degree at Goethe University Frankfurt in Frankfurt am Main. In 2021, he joined the Max Planck Institute for Intelligent Systems and the Hertie Institute for Clinical Brain Research in Tübingen with Prof. Georg Martius and Prof. Daniel Häufle for his PhD in Computer Science, which he completed in 2025.Schumacher’s expertise has also attracted industry attention: he joined MyoLab, a startup based in New York focusing on musculoskeletal control technologies, last year.

    The RIG Outstanding Doctoral Thesis Award highlights emerging researchers whose doctoral work significantly advances robotics research in Germany. Schumacher’s selection underscores the growing importance of combining machine learning, biomechanics, and embodied intelligence to enable the next generation of adaptive robotic systems.