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
Congratulations to our relAI director Gitta Kutyniok!
The world's largest technical professional organization dedicated to advancing technology for the benefit of humanity IEEE has selected Gitta Kutyniok for the elevation to IEEE Fellow, the highest grade of membership in IEEE. Less than 0.1% of voting members are selected for this member grade elevation each year.
The IEEE Fellow Committee recognized her achievements with the following statement: “for contributions to the mathematical theory of artificial intelligence in signal processing and communication”
We are excited to announce that our second call for applications to the fully funded PhD program of our Konrad Zuse School of Excellence in Reliable AI (relAI) is now open.
Spread the word and submit your application by January 15th, 2024 here.
On the 11th and 12th of October, relAI welcomed the new cohort of relAI Master and Doctoral students. The event included informative sessions about relAI and networking activities. At the Munich Data Science Institute (MDSI), TUM, the relAI directors and coordinators presented the relAI program to the new students. The first relAI cohort of students organised a lively interactive session (photo) to welcome and get to know the new students.
Congratulations to the relAI PhD Student Lisa Wimmer, the relAI fellow Bernd Bischl, and the relAI director Stephan Günnemann on the best paper award of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2023).
ECML PKDD is Europe’s top machine learning and data mining conference, with over 20 years of successful events and conferences across the continent. The ECML PKDD 2023 was held in Turin, Italy from the 18th to the 22nd of September 2023.
List of authors and title of the awarded paper:Jonas Gregor Wiese, Lisa Wimmer, Theodore Papamarkou, Bernd Bischl, Stephan Günnemann, David Rügamer
Towards Efficient MCMC Sampling in Bayesian Neural Networks by Exploiting Symmetry
On 14 September, the Munich Data Science Institute (MDSI, TUM) celebrated its official opening at the Science Congress Center in Garching. The event included inaugural words by the Bavarian State Minister for Science and the Arts, M. Blume, and the TUM President, Prof. Dr. T. Hofmann. Top-class scientific lectures from MDSI Members, presentations of outstanding MDSI projects, a panel discussion, and a poster session rounded the program.
The Konrad Zuse School of Excellence in Reliable AI (relAI), a joint project between TUM and LMU funded by DAAD, which had been initiated through an MDSI Focus Topic, was one of the projects highlighted at the opening. relAI Coordinator Dr. Andrea Schafferhans introduced relAI to the audience, giving an excellent overview of its educational and research programs as well as its people. relAI was also widely represented at the poster session by relAI Master students and PhD researchers from the TUM University, who discussed their research projects with the numerous guests of the event, among them, MDSI partners and representatives from industry and other research institutions.
We are proud that our network is constantly growing and welcome the industry partners Infineon and Volkswagen into the relAI family!
One of relAI’s main objectives is to transfer the research results in reliable AI technology to industry. The partnership of relAI with industry not only ensures this transferability, but also contributes to the education of future experts in reliable AI, dedicated to guaranteeing the safety, security, and privacy-preservation in AI-based applications in domains such as autonomous driving (Volkswagen) and AI-based semiconductor solutions (Infineon).
This partnership is mutually beneficial to both, our students and our industry partners: The students have the opportunity to work with renowned companies to gain practical knowledge during projects, workshops and internships.Our partners get to work with talented young scientists from all over the world, with cutting-edge expertise in reliability.
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.