relAI is proud to support the Philosophy of Machine Learning Conference (PhilML'26), which will take place in Munich from October 6 to 9. Tom Sterkenburg, a relAI Fellow, is one of the main organizers of this event.
The conference will address fundamental epistemological, ethical, and social questions related to machine learning through the lens of analytic philosophy. We welcome the following types of work:
1. Research that applies philosophical concepts and methods to gain insights into machine learning.
2. Research that critically reflects on the philosophical and ethical implications of machine learning.
To promote close and productive dialogue, PhilML brings together philosophers and machine learning researchers with a philosophical inclination, encouraging direct engagement with scientific and mathematical details.
Join us for a lively meetup featuring leading researchers from MDSI and relAI at the SAP Labs Munich Campus Auditorium, where we will connect, discuss, and explore new ideas with our industry partner SAP.
🗓️ September 22, 2026, 4:00 - 5:30 pm (doors open at 3:30 pm, talks start at 16:00)
📍 SAP Labs Munich Campus (MUE03), Friedrich-Ludwig-Bauer-Straße 5, 85748 Garching bei München, Auditorium (AE.76)
Bhavatarini Kumaravel(MDSI): A Graph-Based Deep Q-Learning Agent for Grammar-Guided Structural Form-Finding Bhavatarini's supervisor is the MDSI Core Member Prof. Pierluigi D'Acunto, TUM Chair for Structural Design, TUM School of Engineering and Design
The work investigates how graph-based deep reinforcement learning can be combined with a structural grammar in finding novel and materially efficient structural design solutions.
Annika Schneider(relAI): Decision-aligned Evaluation of Uncertainty Quantification Annika is a relAI PhD student at Helmholtz Munich and TUM, supervised by relAI Fellow Dr. Vincent Fortuin, TUM Associate Professorship of AI for Scientific Modelling
This work investigates the question of how probabilistic models should be evaluated to ensure they perform in downstream decisions.
Sameer Ambekar(relAI & MDSI): Adressing Distribution Shifts: The Shift from Static to Thinking-based Vision-Language Models Sameer is a relAI PhD student at Helmholtz Munich and TUM, supervised by relAI Fellow and MDSI Core Member Prof. Julia Schnabel, TUM Chair for Computational Imaging and AI in Medicine
Distribution shifts have remained a persistent challenge over the years, with solutions spanning from domain adaptation to test-time training and, most recently, post-training mechanisms for vision-language models. This is because models inevitably encounter unseen data at inference time, data they were never trained for.
This talk at SAP by Sameer will focus on addressing this problem, tracing it from convolutional architectures to modern vision-language models and reasoning models, and connecting these stages through a consistent pattern: models that allocate additional computation at test time, whether through adaptation or reasoning, generalize more reliably than those relying solely on fixed, pre-trained parameters. Sketching through these topics from his PhD research, the talk will provide an overview of addressing unseen data at test time through training, reasoning, and post-training mechanisms.
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From July 28 to July 31, 2026, relAI hosted the second relAI International Summer School at LMU. This event focused on promoting educational exchange aimed at developing reliable AI and exploring current trends in the field.
Last week, our industry partner, QuantCo, hosted a networking event with relAI at their new Munich office.
The relAI students had a wonderful evening filled with engaging conversations and delicious food. They had the opportunity to meet colleagues from QuantCo's AI, and engineering teams and learned about how the company develops scalable systems to transform messy, real-world data into impactful decisions.
We are pleased to share relAI’s contribution to the European Embodied Robotics Week, whichtook place last week in Munich. The event was organizedby RoboTUM together with START Munich and the ESRA (European Student Robotics Association) network.
The Robotics Festival convened a diverse range of stakeholders from the European robotics and physical artificial intelligence ecosystem. Specialists, students, and robotics enthusiasts participated in city-wide events, including open houses at robotics laboratories, makerspaces, and studios throughout Munich, as well as a hackathon.
The event ended with a summit featuring talks and panels from leaders in embodied intelligence. relAI was represented in the panel discussion “Dexterity and Manipulation for robotics” by relAI Fellow Prof. Khadiv.
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Last week, the relAI family gathered for our annual retreat in the beautiful and serene Bad Kohlgrub, from June 17th to 19th. During this time, relAI students, fellows, directors, and management came together to share ideas and visions for the future of our school, the role of AI in education, and the future of science in the era of agentic AI.
The program included keynote talks from relAI fellows Enkelejda Kasneci, Sandra Hirche, Niki Kilbertus, and Christoph Kern. It also featured lightning talks by relAI students, group discussions, and fellow/student one-on-one sessions. Additionally, there was plenty of time for networking and social activities.
Keynote by Enkelejda KasneciKeynote by Sandra HircheKeynote by Niki KilbertusKeynote by Christoph Kern
In the one-on-one sessions, relAI fellows and students connected directly to discuss their research experiences, career paths, and future aspirations. These conversations provided a unique mentorship opportunity, often sparking new perspectives for both mentors and mentees.
This year's group discussions focused on questions about the two strategic pillars that are currently reshaping the landscape of reliable AI:
Future of Science in Times of Agentic AI
How do agentic workflows change the way we conduct and validate our research?
What are the theoretical and practical requirements for genuinely dependable autonomous systems?
AI for Next Generation Education
What roles will AI and human teachers play moving forward? How can we lead the adoption and ethical use of AI technologies?
How can we establish standards for reliability in pedagogical AI tools?
A highlight of this year’s retreat was the presentation of the final relAI certificates to MSc and PhD students who completed the program. This moment provided an opportunity to reconnect with relAI alumni and learn about their career paths after leaving relAI.
This inspiring retreat strengthened our community and paved the way for our efforts to shape the future of reliable AI.
A big thank you to everyone who participated and contributed to making this event a success!
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On June 8, 2026, TUM hosted the International Symposium 'Future Learning: Global Perspectives, European Pathways' as part of the new relAI research area Learning & Instruction.
Frontier AI systems have recently solved IMO problems, discovered new mathematical constructions, and resolved open Erdős problems. Yet a more mundane question remains: 🤔how should a working mathematician actually use these tools day to day?
In this talk, titled “The Agentic Researcher: Turning AI Coding Agents into Research Assistants” Emil Partow, PhD Student of our relAI Director Prof. Gitta Kutyniok presented a recent paper from Prof. Pokutta (Zuse-Institut Berlin) that offers a concrete answer. The authors propose a five-level taxonomy of AI integration into research, ranging from classical work without AI to fully autonomous research loops. They have implemented this idea within an open-source framework.
Following a detailed presentation by Emil Partow, members of relAI and Prof. Kutyniok's research group gathered to discuss this forward-looking topic. The presentation explained the open-source tool that implements core research "commandments" (such as preventing the falsification of experimental data) via a practical, actionable loop. Participants then discussed how AI agents are already shaping research methodologies, what is required to implement these workflows successfully, and how to ensure human oversight remains at the center of the process. Emil also shared a practical case study demonstrating the tool in action, sparking a broader reflection on the evolving role of AI in modern research.
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🔮How will artificial intelligence (AI) influence the future of learning?
