relAI Director Gitta Kutyniok elected NAAI Member

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🥂Congratulations!

We are proud to announce that our relAI Director Gitta Kutyniok has been invited to become a member of the US National Academy of Artificial Intelligence (NAAI). NAAI is committed to advancing artificial intelligence by fostering collaboration among leading experts and promoting innovative research and development.

The election acknowledges Gitta Kutyniok's distinguished contributions to applied harmonic analysis, compressed sensing, and artificial intelligence. This honor recognizes her leadership as the Bavarian AI Chair for Mathematical Foundations of Artificial Intelligence at Ludwig-Maximilians-Universität München (LMU Munich), which has significantly advanced research and collaboration in these fields. Additionally, NAAI greatly appreciated her recognition as a SIAM Fellow in 2019 and an IEEE Fellow in 2024, which highlights her outstanding accomplishments and the high regard in which she is held by her peers. 

relAI is proud to support the opening ceremony of the project “Next Generation AI Computing (gAIn)"! This collaboration between LMU and TUM in Bavaria and TU Dresden in Saxony is financially supported by the Bavarian State Ministry of Science and the Arts, as well as the Saxon State Ministry for Science, Culture, and Tourism. The goal of the project is to develop a comprehensive, mathematics-based concept for the next generation of "Green AI" systems. The focus will be on application-based AI hardware-software combinations aimed at maximizing energy efficiency, trustworthiness, and legal compliance.

The event will feature keynotes from Minister Blume (Bavaria) and Minister Gemkow (Saxony), and a scientific lecture by Prof. Dr. Wolfram Burgard (UTN), as well as general information about the project.

For the Konrad Zuse Schools of Excellence in Artificial Intelligence, the project presents a significant opportunity to collaborate, as relAI Director Gitta Kutyniok and Stefanie Speidel, deputy director of the Zuse School SECAI, are both Principal Investigators on the project.

 

🎉The 8th edition of DataFest Germany will be held at Ludwig-Maximilians-Universität in Munich from 28 March to 30 March 2025. relAI is proud to support the event organization again this year. Additionally, a team of relAI students will participate in this exciting competition and networking opportunity.

The event is an annual data-driven competition, commonly referred to as a “hackathon,” that alternates between Mannheim and Munich. It is organized in collaboration with partners from industry and research institutions.

Datafest Germany is a celebration that follows upon the model DataFest™, organized by the American Statistical Association. The world's first DataFest took place at the University of California in 2011. Since then, many universities took up the DataFest format.

Learn more about DataFest Germany in this link.

The Roland Berger Foundation (RBS) and TUM have begun a collaboration to promote the AI skills of socially disadvantaged children and young people. RBS works with 70 partner schools throughout Germany to provide scholarships to talented primary school pupils from the second grade onwards from socially disadvantaged families.

relAI Fellow Enkeledja Kasneci is the scientific director of the project. The scholarship holders learn how to use AI responsibly and reflectively. AI tools are also being developed to better support children and young people with difficult starting conditions

For more information, please visit the websites of Roland Berger Foundation and TUM.

The European legal initiative to regulate AI (Artificial Intelligence Act) poses a particular challenge to small and medium-sized enterprises (SMEs) and start-ups that want to benefit from artificial intelligence and pursue innovations. Bavarian AI Act Accelerator, a new project funded by the Bayerisches Staatsministerium für Digitales and coordinated by the appliedAI Institute for Europe gGmbH, is designed to support companies in fulfilling the new requirements and, therefore, lower barriers to the use of artificial intelligence.

Principal contributors of the project include relAI directors Prof. Dr.  Gitta Kutyniok and Prof. Dr. Stephan Günnemann,  relAI fellow Prof. Dr. Mark Zöller, as well as scientists from the Technical University of Munich (TUM) and the University of Technology Nuremberg (UTN), who provide the necessarily high degree of interdisciplinarity.

relAI director Prof. Dr. Gitta Kutyniok leads the scientific part of the project. One of the main goals is to develop a system for automatic, and hence easy and fair, verification with the EU AI Act. This requires the following steps:
🔹Derive a profound legal understanding of the different terminologies.
🔹Develop a formalization/mathematization of the articles.
🔹 Build a system for automatic verification.

🛫 Our director, Gitta Kutyniok, gave a talk and joined the panel discussion at the Kick-Off event last week (photo) as the scientific lead of the project.   

Excerpts taken from:

After Stargate and DeepSeek, which technological developments will influence the future of the AI race? What implications does this hold for Germany and Europe? Have we constrained ourselves too soon with the AI Act? In an interview on the “Plattform Lernende Systeme” website, Prof. Dr. Gitta Kutyniok, Director of relAI and member of the Platform, discusses the current dynamics and explains how mathematics can enhance the comprehensibility of AI results.

Watch the interview here.

The Saxon-Bavarian AI project GAIn – Next Generation AI Computing is a pilot project tackling new AI hardware and software concepts to reduce energy consumption and increase reliability for different applications such as surgical robotics. It builds on the foundation of the Cluster of Excellence CeTI, the 6G-life research hub, and the Konrad Zuse Schools of Excellence SECAI and relAI. The project aims to address key challenges in energy consumption, predictability, reliability, and legal implementation. A core objective is to significantly reduce the energy consumption of AI-based applications while enhancing their predictability and reliability for different applications such as surgical robotics.

The project has now been officially launched. Together with Frank Fitzek (TU Dresden), Gitta Kutyniok (LMU, relAI) and Holger Boche (TUM), Stefanie Speidel (TU Dresden, SECAI) hosted the kick-off meeting of the project.  The cooperation across federal states will strengthen Germany's technological sovereignty and contribute to the international leadership role of Saxony and Bavaria in central computing technologies.

Excerpts from the TUD press release AI project "GAIn" with TUD participation aims to propel Saxony and Bavaria to an international leadership role in computing technologies, of the National Center of Tumor Disease Dresden (NCT)  GAIn (2024 – 2027)  and of SECAI news https://secai.org/content/news/56

relAI warmly welcomes LMU Professor David Rügamer to our school. David heads the Data Science Group at LMU, and he is also a Principal Investigator at the Munich Center for Machine Learning (MCML).

Prof. Rügamer works on fundamental topics within the relAI research area Mathematical and Algorithmic Foundations applied to neural networks, such as symmetries, sparsity, and uncertainty quantification in deep neural networks. Additionally, his work is also relevant to the Algorithmic Decision-Making relAI research topic. relAI will benefit from his research experience and, furthermore, from his contributions to our Curriculum, including lectures.. 

In this interview, relAI Fellow Daniel Rückert, recently awarded Germany’s highest research distinction, the Gottfried Wilhelm Leibniz Prize, shares his insights on the role of artificial intelligence (AI) systems in medicine.

Prof. Rückert discusses the significant potential of AI in early disease diagnosis, prevention, and personalized treatment, and explains his contributions to AI-assisted analysis of X-ray and MRI images, focusing on the detailed detection of abnormalities and the quick reconstruction of high-quality images. Notably, he emphasizes that reliability and explainability are essential aspects of AI systems in medicine and one of his research topics at relAI.

Follow this link to read the complete interview.

This month, a team of 13 talented master and PhD students from our graduate school in reliable AI (relAI) showcased their quantitative skills and teamwork in an exciting estimation competition. The participants had 30 minutes to work on 13 estimation challenges, such as "What is the average discharge of the Isar when it meets the Donau in m^3/s?"

The spirit of competition and learning was truly inspiring. Check out the photo of our team, proudly representing relAI.