relAI welcomes new Fellows

People

We are delighted to welcome four exceptional fellows to relAI: Nassir Navab, Solveig Vieluf, Tobias Lasser and Jochen Kuhn.  

Each of them brings their own expertise and insights that will further enrich our research agenda, educational offers, and scientific community. They are dedicated to making significant contributions to the advancement of reliable AI, particularly in Medicine & Healthcare and AI in Education areas.  

Nassir Navab is a full professor and director of the Laboratories for Computer Aided Medical Procedures at TUM and adjunct professor at John Hopkins University. One focus of his research is AI assisted Surgery, where reliable methods are a key requirement for both clinicians and patients.  

Solveig Vieluf is a professor of AI-based telemonitoring in the field of cardiology at LMU. Previously, she has also worked on epilepsy and aging research. She uses methods from explainability to explore influence factors on model performance. 

The research of Tobias Lasser is focused on computational imaging and inverse problems in medicine and healthcare. In his work on clinical decision support using AI, he works on prioritization of critical cases for treatment.  

Jochen Kuhn works on the intersection of AI and education, in particular on the use of these future technologies to foster learning and teaching in STEM disciplines. He is a professor of Physics education at LMU. Reliability is important in his research, particularly the role of bias and inaccurate information from AI chatbots on learning and teaching.  

Join us in welcoming these four to the relAI community! 

We are proud to announce that the German Radiological Society (Deutsche Röntgengesellschaft) has awarded the Alfred Breit Prize 2024 to our relAI fellow Prof. Julia Schnabel. The prize honors outstanding work and developments in the field of radiological research that have significantly contributed to progress in cancer therapy.

Julia Schnabel is Professor for Computational Imaging and AI in Medicine at the Technical University of Munich TUM (Liesel Beckmann Distinguished Professorship), and Director at the Institute for Machine Learning in Biomedical Imaging at Helmholtz Munich (Helmholtz Distinguished Professorship). Since 2015, she has also been Professor of Computational Imaging at King's College London.

Prof. Schnabel works in the field of medical image processing and machine learning. Her research focuses on the areas of intelligent imaging up to clinical evaluation, including complex motion modeling, image reconstruction, quality assurance, segmentation, and classification applied to multimodal, quantitative, and dynamic imaging.

Congratulations!

Are you interested in frontier AI systems, their astonishing capabilities and risks for humanity? Then join us for a thought-provoking deep dive and exclusive OpenAI Live Q&A on AI safety. 

  • Date: Wednesday, May 8th, 2024 | 19:00 – 20:30 
  • Location: Room B006, Department of Mathematics (Theresienstr. 39) or online 
  • Language: English 

Agenda: 

  • 19:00 – 19:05: Doors open 
  • 19:05 – 19:30: Introduction to AI Safety 
  • 19:30 – 20:15: Presentation & Live Q&A with OpenAI researcher Jan H. Kirchner, co-author of weak-to-strong generalization paper 
  • 20:15 – 20:30: Closing talk – What can we do? 
  • 20:30 – onward: Optional socializing and small group discussions with free drinks and snacks. 

Please register on the following webpage and prepare your questions! 

Last week, our relAI students presented their research to the relAI industry partners in a series of industry workshops. Four events took place, each centered around one of  the four relAI’s research areas: Mathematical & Algorithmic foundations, Algorithmic Decision-Making, Medicine & Healthcare and Robotics & Interacting Systems. 

We are thrilled that this event was so well received both by the students and the industry partners! Following short lightning talks, intriguing discussions around reliability of AI took place in smaller breakout groups.  

The industry workshops are part of relAI´s cross-sectional training and aim to facilitate the exchange of insights and expertise between academia and industry. The engagement from both our students and industry fellows emphasized the significance of bridging academic excellence with real-world applications, particularly when addressing the evolving challenges in AI reliability. 

We are excited to announce that our call for applications to the relAI MSc program is now open! 

The novel, innovative relAI MSc program is an addition to a regular MSc program at Technical University of Munich (TUM) or Ludwig Maximilians University (LMU), offering comprehensive cross-sectional training in reliable AI, including scientific knowledge, professional development courses, and industrial exposure. Funded applicants receive a scholarship of up to 934€ and additional support such as travel grants for home travel.   

relAI, funded by the German Academic Exchange Service (DAAD), is embedded in the unique transdisciplinary Munich AI ecosystem, combining the expertise of the two Universities of Excellence TUM and LMU of Munich.  

We highly encourage you to apply if you:   

  • hold an excellent Bachelor’s degree in computer science, mathematics, engineering, natural sciences or other data science/machine learning/AI related disciplines,  
  • are accepted to a MSc program in said disciplines at either TUM or LMU starting in spring or fall 2024, or have applied there (Acceptance necessary before joining relAI) 
  • have a genuine interest to study reliable AI covering aspects such as safety, security, privacy and responsibility in one relAI’s research areas Mathematical & Algorithmic foundations, Algorithmic Decision-Making, Medicine & Healthcare or Robotics & Interacting Systems, and
  • can certify proficiency in English on C1 or higher level.  

📆 Application Deadline: June 17th, 2024  

🔗 Apply now: www.zuseschoolrelai.de/application 

We are thrilled to announce our new industry partnership with SAP!

The new collaboration will strengthen the school's expertise in Business AI, and will contribute to translate our AI research into the development of reliable AI systems. You can read below the views of SAP members on this exciting alliance between relAI and SAP.

We are thrilled to extend our collaborative efforts on research-driven product innovation with the Technical University of Munich and the Munich ecosystem through our new partnership with the Konrad-Zuse-School of Excellence in Reliable AI. This expansion not only consolidates our portfolio of AI-related applied research projects, but also fosters a more profound knowledge exchange and talent engagement on topics around the development of reliable AI systems and Business AI.

- Dr. Katharina Wollenberg and Dr. Rüdiger Eichin, Industry-University Collaboration, SAP

At SAP, we are committed to help our customers leverage AI to create tremendous business value. We specialize in Business AI: AI that is relevant since it’s embedded in enterprise business applications and processes from day one; that is reliable since we train, ground, and adapt AI on companies’ business data and context; and that is responsible by design, following SAP’s rigorous AI ethics, privacy, and security practices. We are delighted to join the Konrad Zuse School of Excellence in Reliable AI and look forward to collaborating with academica to drive the development and delivery of relevant, reliable, responsible Business AI.

- Dr. Johannes Hoffart, CTO AI, SAP

Related social media posts: X & LinkedIn

Image: SAP Labs Munich Campus at Campus Garching

We are delighted to welcome five exceptional fellows to relAI: Alin Albu-Schäffer, Angela Schoellig, Björn W. Schuller, Christian Wachinger, and Stephan Bauer. 

Each of them brings their own expertise and insights that will further enrich our research agenda and scientific community. From diverse backgrounds in Medicine, Robotics and Data Science, they are dedicated to making significant contributions to the advancement of reliable AI. 

Alin Albu-Schäffer is director of the Institute of robotics and Mechatronics at the DLR – German Aerospace Center and professor at TUM. Methods of safe AI are attributed special importance in robotics, where artificial intelligence interacts with the physical world through complex machines. His research offers both interesting application fields and new questions for reliable AI. 

Angela Schoellig recently moved to Munich from Toronto upon being awarded an AI Humbold professorship, an award which aims to attract top international scientists to German universities. Further, she is a member of the board of directors at MIRMI. Her Chair of Safety, Performance and Reliability for Learning Systems at TUM perfectly aligns with the research topics of relAI.  

Björn W. Schuller, professor for health informatics at TUM and Klinikum rechts der Isar, works on responsible methods for medicine and healthcare. He has a background in speech recognition and works as the CSO of the Audio Intelligence company audEERING. 

Christian Wachinger is professor for AI in radiology at Klinikum rechts der Isar. A common motif of his research is “Bias and Fairness”, but his research also concerns causal inference and application of AI methods to medicine and healthcare. 

The final addition to relAI is Stephan Bauer, who is senior group leader at Helmholtz and associated professor for Algorithmic Machine Learning & Explainable AI at TUM. His research focuses on causality and deep learning. He also has background in robotics and healthcare as domain application areas of AI. 

Join us in welcoming these five to the relAI community! 

Please take a look at the excellent interview with the director of relA Prof. Günnemann at TUM. The interview, titled “The reliability of AI will play a decisive role in Germany”, emphasizes the transformative focus that our school's main topic plays in technology.