relAI welcomes new Fellows

Fellows

relAI is proud to announce the addition of five exceptional fellows to the school. Enkelejda Kasneci (TUM), Gjergji Kasneci (TUM), Björn Ommer (LMU), Tom Sterkenburg (LMU), and Abdalla Swikir (TUM) have each made significant contributions to their respective fields and bring a wealth of knowledge and experience to our family.

The research topics of the new fellows tackle essential aspects of the field of reliable AI. Their work ranges from the study of human-computer interaction and semantic scene understanding to the study of fairness and inductive bias in machine learning as well as safe learning in robotics. Their engagement in the school's research and educational activities will contribute to the reliable application of AI in real-life scenarios, such as improving user experience in digital interfaces and enhancing the safety of autonomous systems.

Enkelejda Kasneci is a Distinguished Professor (“Liesel Beckmann Distinguished Professorship”) for Human-Centered Technologies for Learning at the TUM School of Social Sciences & Technology. Her research focuses on Human-Computer Interaction and developing AI systems that sense and infer the user’s cognitive state, expertise, actions, and intentions based on multimodal data.

Gjergji Kasneci holds the Chair for Responsible Data Science at TUM School of Computation, Information & Technology. His research focuses on transparency, robustness, bias, and fairness in machine learning algorithms, incorporating ethical, legal, and societal considerations.

Abdalla Swikir is a Senior Scientist and Teaching Coordinator at the TUM Munich Institute of Robotics and Machine Intelligence (MIRMI). His research in safe learning for robotic control and autonomous systems targets the enhancement of reliability and safety, ensuring these technologies can effectively function in dynamic and critical environments.

Björn Ommer is Head of the LMU Computer Vision & Learning Group. His research interests include semantic scene understanding and retrieval, generative AI and visual synthesis, explainable AI, and self-supervised metric and representation learning. Moreover, he is applying this basic research in interdisciplinary projects within neuroscience and the digital humanities.

Tom Sterkenburg is an Emmy Noether junior research group leader at the Munich Center for Mathematical Philosophy at LMU Munich. His Emmy Noether project, “From Bias to Knowledge: The Epistemology of Machine Learning", is concerned with clarifying the fundamental concept of inductive bias in machine learning.

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!

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! 

We are thrilled to congratulate relAI fellow Prof. Sami Haddadin for his elevation to IEEE fellow. This is the highest membership degree of IEEE, the world's largest technical professional organization dedicated to advancing technology for the benefit of humanity.  

This prestigious distinction was awarded to the director of the TUM Munich Institute of Robotics and Machine Intelligence (MIRMI) “for his contributions to robot safety, tactile robots, and interaction control”. 

Our Congratulations! 

Congratulations to relAI fellows Prof. Sandra Hirche and Prof. Claudia Eckert on receiving the prestigious 2023 Heinz Maier-Leibnitz Medals from TUM.

We are excited that the TUM honors the exceptional achievements of Prof. Dr. Claudia Eckert and Prof. Dr.-Ing. Sandra Hirche with the 2023 Heinz Maier-Leibnitz Medals. This annual award of the TUM was presented to the relAI fellows at the recent Dies Academicus in December 2023.  

In the Laudati, Senior Vice President Prof. Gerhard Kramer acknowledged the outstanding contributions of Prof. Dr. Claudia Eckert "at her chair at TUM and as head of the Fraunhofer Institute for Applied and Integrated Security AISEC with the protection of IT systems against hacker attacks." Prof. Dr.-Ing. Sandra Hirche was recognized for her "groundbreaking work" in control engineering and systems theory. 

A big congratulations to them both! These well-deserved awards are a testament to their dedication and impact in their respective fields, particularly to reliable AI.  

Please find more information about this prestigious price from TUM: https://www.tum.de/en/about-tum/facts-and-figures/awards-and-honors/awards-presented-by-the-technical-university-of-munich/heinz-maier-leibnitz-medal  

relAI is happy to welcome five new relAI fellows from TUM, LMU and the research center Helmholtz AI.

The expertise of the new fellows on reliability AI  will strengthen the relAI research and education, particularly on the Mathematical and Algorithmic Foundations relAI Focus area. New fellow Prof. Dr. Daniel Cremers (TUM) is specialised in computer vision and has worked in the AI field for many years, covering aspects of reliable AI. Prof. Dr. Reinhard Heckel (TUM) is interested in developing methods that are robust to worst case perturbation and most importantly to distribution shifts, an integral aspect of reliable AI. Prof. Dr. Johannes Maly (LMU) ´s research is naturally aligned with the goals of relAI. It focuses on understanding how to leverage intrinsic model or data structure and how the loss of information caused by digital processing (quantization) affects theoretical results. LMU fellow Prof. Christoph Kern works at the intersection of statistics, (computational) social science, and data science. His research goals overlap considerably with the research areas and themes of relAI. The research of Dr. Vincent Fortuin (Helmholtz AI) on uncertainty quantification with Bayesian methods also fits perfectly within relAI, especially with the central theme of safety. The contribution of the new relAI fellows to research support, seminars, and lectures will enrich the relAI curriculum and advance the theoretical research of the relAI field.

 

We are proud to report that our relAI fellow Prof. Pramod Bhatotia has received the EuroSys 2023 Jochen Liedtke Young Researcher for his work on systems research.

The EuroSys Jochen Liedtke Young Researcher Award rewards junior European researchers who have demonstrated exceptional creativity and innovation in systems research, broadly construed. The selection committee chooses the recipient based on demonstrated contributions that have had impact and are creative and innovative, along with demonstrated promise for making lasting and fundamental contributions to the field. 

The award is named in honor of Jochen Liedtke, one of the most prominent researchers on microkernel architecture. His work culminated with the L4 microkernel design, which rethought inter-process communication from the ground up. The award is given annually at the EuroSys conference, in memory of Jochen and his fundamental contributions to the systems community.

Find more information here.