Munich AI Lecture of Prof. Dr. Jean-Luc Starck

Events

e.g. Welcome Week, Retreat, DAAD Inauguration,…

It is our great pleasure to announce the next Munich AI Lecture featuring Prof. Dr. Jean-Luc Starck, Director of Research and head of the CosmoStat laboratory at the Institute of Research into the Fundamental Laws of the Universe, Département d'Astrophysique, CEA-Saclay, France. The lecture is organized by relAI director Prof. Dr. Gitta Kutyniok, and co-hosted by Prof. Dr. Jochen Weller, with support of BAIOSPHERE, the Bavarian AI Network.

Event Details:

  • Speaker: Prof. Dr. Jean-Luc Starck
  • Title: Unveiling the Cosmos: Deep Learning Solutions to Inverse Problems in Astrophysics
  • Date and Time: Tuesday, 18. February 2025 from 17:00 pm to 18:30 pm
  • Location: Senatssaal, LMU Munich, Geschwister-Scholl-Platz 1, Munich 

    Prof. Starck will speak about how inverse problems in astrophysics, such as image reconstruction or gravitational lensing data analysis, have traditionally relied on sparsity-based techniques to recover underlying physical structures from incomplete or noisy data. Deep learning methods are now replacing these classical approaches, offering unprecedented performance gains in accuracy and efficiency. Despite their success, deep learning methods introduce new challenges, including interpretability, generalization across diverse astrophysical scenarios, and robustness to observational biases. In this talk, the speaker will explore the transition from sparsity-driven methods to deep learning-based solutions, highlighting both the opportunities and pitfalls of this paradigm shift. Prof. Starck will discuss recent developments, applications to astrophysical data, and future directions for addressing the emerging challenges in this rapidly evolving field.

    To read more information about the event and the speaker, visit this weblink.

    relAI is a co-organiser of the Munich AI lectures. Find more info on this and other upcoming events on the Munich AI lectures home page.

    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.

    We are pleased to share that on January 29, 2025, relAI will join the opening ceremony of our partner AI-HUB@LMU  to celebrate its founding. AI-HUB@LMU is a platform that, for the first time, unites all 18 faculties of Ludwig-Maximilians-Universität München as a joint scientific community and aims to advance research, teaching, and transfer in artificial intelligence and data science at LMU.  

    As part of our commitment to fostering collaboration and innovation, relAI supports the organization of this significant event. The event will be honoured by inaugural remarks from representatives of the university and government. All 18 faculties will then present their highlights in AI and data science in keynote talks, panel discussions, pitch talks, and presentations. Check this link for the full program: https://www.ai-news.lmu.de/grand-opening-ai-hub.  

    Multi-Head Attention has become ubiquitous in modern machine learning architectures, but how much efficiency can still be gained? This question was the focus of Dr. Maximilian Baust’s talk, "Beyond Transformers: Why Beating Multi-Head Attention is Hard."

    In his presentation, Dr. Baust explored potential solutions for improving efficiency, ranging from implementation strategies and algorithmic modifications to new architectures, including spiking neural networks.

    Dr. Maximilian Baust serves as Director of Solution Architecture Industries EMEA at NVIDIA and is also an industry mentor for one of relAI’s PhD students.

    We extend our gratitude to Dr. Baust for sharing his insights and to our director, Gitta Kutyniok, for inviting him to relAI.

    The recent relAI Collab Accelerator Workshop brought together researchers to share their work, explore new ideas, and identify potential collaborations. Here's a brief overview of the event:

    The day began with the participants pitching their research topic from 9:00 to 11:00, followed by a coffee break until 11:15. After the break, participants engaged in one-to-one sessions until 14:00, followed by lunch, discussion, and feedback.

    Participants contributed diverse topics in the field of Machine Learning and Artificial Intelligence. Mohamed Amine Ketata discussed Generative AI for Graphs, Max Beier presented on Learning Operator of Dynamical Systems, Richard Schwank explored Robust Aggregation through the Geometric Median, and Yurou Liang delved into Differentiable Learning for Causal Discovery.

    The workshop was fertile ground for generating new research ideas and possible collaborations. During the one-to-one discussions, participants identified several projects for cooperation, such as principled modifications of loss functions to enhance robustness against outlier data rows.

    Participants gained new insights into their research during the event. For example, one participant discovered a probabilistic approach to their forecasting issue without relying on a model. Another learned about structure learning as it applies to tabular data, which provided a temporal interpretation of the data. One researcher was challenged about the convexity of their problem. Discussions highlighted intriguing applications of median aggregation techniques to abstract spaces, connecting concentration inequalities with uncertainty quantification.

    The relAI Collab Accelerator Workshop was an enriching experience, offering a platform for researchers to connect, share insights, and pave the way for future collaborations. The feedback during this first iteration will help refine the format and make it even more engaging. We are looking forward to the next iteration!

    relAI thanks Max Beier and Richard Schwank for their initiative and the organization of the event.

    We are happy to invite you to the upcoming Munich AI Lecture featuring two distinguished researchers Prof. Holger Hoos from RWTH Aachen University and Prof. Franca Hoffmann from California Institute of Technology. The lecture is organized by the Chair of Mathematics of Information Processing with support by MCML.

    In the first talk, “Dynamics of Strategic Agents and Algorithms as PDEs“, Prof. Hoffmann will speak about dynamics of interactions between algorithms and a population.

    In the second talk, “Learning, reasoning and optimisation: Adversarial robustness of neural networks”, Prof. Hoos will discuss robustness of neural networks and its verification.

    Event Details:

    • Speakers: Prof. Dr. Holger Hoos and Prof. Dr. Franca Hoffmann
    • Date and Time: December 17, 2024, 16:00 CET (16:00-17:00 talk by Prof. Hoffmann and 17:30-18:30 talk by Prof. Hoos – We will have a small break with coffee/tea and snacks in between)
    • Location: Senatssaal, LMU Munich, Geschwister-Scholl-Platz 1, Munich 

    Bio Franca Hoffmann

    Franca Hoffmann obtained her master’s in mathematics from Imperial College London (UK) and holds a PhD from the Cambridge Centre for Analysis at University of Cambridge (UK). She held the position of von Kármán instructor at Caltech from 2017 to 2020, then joined University of Bonn (Germany) as Bonn Junior Professor and Quantum Leap Africa in Kigali, Rwanda (African Institute for Mathematical Sciences) as AIMS-Carnegie ResearchChair in Data Science, before arriving at the California Institute of Technology as Assistant Professor in 2022.

    Bio Holger Hoos

    Holger H. Hoos holds an Alexander von Humboldt professorship in AI at RWTH Aachen University (Germany), where he also leads the AI Center, as well as a professorship in machine learning at Universiteit Leiden (the Netherlands) and an adjunct professorship in computer science at the University of British Columbia (Canada). He is a Fellow of the Association of Computing Machinery (ACM), the Association for the Advancement of Artificial Intelligence (AAAI) and the European AI Association (EurAI), past president of the Canadian Association for Artificial Intelligence, former editor-in-chief of the Journal of Artificial Intelligence Research (JAIR) and chair of the board of CLAIRE, an organization that seeks to strengthen European excellence in AI research and innovation (claire-ai.org).

    relAI is a co-organiser of the Munich AI lectures. Find more info on these other upcoming events on the Munich AI lectures home page.

     

    Save the date!

    We are pleased to invite you to the upcoming Munich AI Lecture featuring renowned researcher Prof. Dr. Helmut Bölcskei hosted by our relAI director Prof. Dr. Gitta Kutyniok, Bavarian AI Chair for Mathematical Foundations of Artificial Intelligence at LMU.

    Deep neural networks have led to breakthrough results in numerous practical machine learning tasks. In the lecture “The Mathematical Universe behind Deep Neural Networks,” Prof. Dr. Bölcskei will take us on an exciting journey through the mathematical universe behind these practical successes, elucidating the theoretical underpinnings of deep neural networks in functional analysis, harmonic analysis, complex analysis, approximation theory, dynamical systems, Kolmogorov complexity, optimal transport, fractal geometry, mathematical logic, and automata theory.

    Event Details:

     • Speaker: Prof. Dr. Helmut Bölcskei

    • Date and Time: November 25th, 2024, 5.15 pm

    • Location: Große Aula der LMU (Geschwister-Scholl-Platz 1, Room 120, 80539 München)

    Helmut Bölcskei is a Professor of Mathematical Information Science at ETH Zurich and has been a Principal Investigator at the Lagrange Mathematics and Computing Research Center in Paris since 2021. After earning his degrees from Vienna University, he completed a postdoctoral fellowship at Stanford University and has held visiting researcher positions at many leading institutions. In addition to his academic achievements, he is also a successful entrepreneur. Professor Bölcskei has received numerous awards and prestigious fellowships and continues to serve as Editor-in Chief for some of the field's most distinguished journals.

    Learn more about it here.

    From 28 to 30 October, the second annual meeting of the three DAAD Zuse Schools of Excellence in Artificial Intelligence, ELIZA (Darmstadt), SECAI (Dresden), und relAI (Munich) took place in Munich.

    The meeting kicked off on the 28th with a work-meeting of the Zuse Schools directors and coordination teams, the chairman of the Zuse Schools Advisory Board, as well as representatives of BMBF and DAAD. The main event, which followed on the 29th, celebrated the three Zuse Schools’ second anniversary with a rich program featuring welcome speeches, academic and industry keynotes, talks by Zuse School students, and a stimulating panel discussion.

    The celebration on the 29th was opened by inspiring welcome addresses from Prof. Dr. Gerhard Kramer, Senior Vice President for Research and Innovation, TUM, Prof. Dr. Hans van Ess, Vice President for Research, LMU, Dr. Kai Sicks, DAAD Secretary General,  MinR’in Dr. Lisette Andreae, Head of Unit European Higher Education Area, Internationalization, BMBF and MinDir Dr. Rolf-Dieter Jungk, Bavarian State Ministry for Science and the Arts (StMWK). relAI Fellow Prof. Björn Ommer delivered a brilliant keynote talk on the latest research on Generative AI. The industry keynote by Dr. Ahmed Sayed, Head of EMEA Emerging Technologies, AWS, provided an insightful overview of the industry applications of AI.  The four talks from students of the three Zuse Schools showcased the excellent research carried out by the schools. The program was rounded off with an engaging panel discussion about the topic “Reliability in times of generative AI”, featuring a diverse range of perspectives and voices.

    The event concluded on the 30th with a Dialogue session, “My academic and professional future as a Zuse Schools graduate in Germany – chances and challenges” and the Advisory Board Meeting.

    We are thankful to all the speakers and contributors who made the meeting a success, and to BMBF and DAAD for their support of the Zuse Schools.

    Photo on the right side: DAAD / Siegfried Michael Wagner

    On 30 October 2024, the relAI Scientific Advisory Board (SAB) met in Munich. Throughout the Meeting, SAB Members talked to relAI Directors and Fellows, Students, and the Management Team to gain insights into the relAI program from various perspectives within the relAI family. 

    The SAB members shared their extensive experience from numerous international research projects. They advised relAI on the future directions of the program, suggesting strategies for optimizing internal structures and expanding our network.

    We extend our heartfelt gratitude to all SAB members for their time, insights, and invaluable contributions to the relAI program.  

    Meeting with relAI Directors and Fellows
    Break time discussions and posters
    Meeting with relAI Students

    On 9 October, we had the pleasure of welcoming the new cohort of relAI students to our school.

    The day began with a warm introduction from relAI directors, Gitta Kutyniok and Stephan Günnemann, followed by an informative session from our coordinators team, covering the key organizational aspects of relAI.

    The students spent the afternoon getting to know each other in different games and engaging exchange activities, organized by the students representatives Ole Petersen and Johanna Topalis. We wrapped up the day with a delightful dinner, and insightful discussions.  Welcome to relAI, new members! We’re excited to have you on board!