18.11.2024

©LMU
Several MCML PIs Receive BMBF Funding
Funding of Two New Joint Projects
The BMBF is funding two new joint projects with several MCML researchers involved. One teaches AI models causal relationships, the other refines the tactile abilities of robots.
CausalNet: AI that Understands Cause and Effect
The CausalNet project aims to advance machine learning (ML) by integrating causal reasoning, moving beyond current models that rely solely on correlations. This approach promises greater reliability and performance, particularly in fields like medicine, where understanding cause-and-effect relationships could enable targeted therapies.
Funded with nearly €2 million by the German Federal Ministry of Education and Research (BMBF), CausalNet will develop novel methods for embedding causality into ML, working with experts from LMU, TUM, KIT, Helmholtz AI, and Economic AI GmbH – including MCML PIs Stefan Feuerriegel (spokesperson of the project), Stefan Bauer, and Niki Kilbertus. The project will tackle challenges in high-dimensional environments using tools from representation learning, statistical efficiency, and specialized ML paradigms, with a focus on open-source outputs.
GeniusRobot: Enhancing Robotic Vision and Grasping with AI
The other project focuses on improving robotic manipulation using generative AI. MCML PIs Gitta Kutyniok and Björn Ommer are developing interpretable AI models that predict tactile information from visual data, enabling robots to dynamically adapt their grip.
The project leverages multimodal AI to integrate and interpret sensory inputs, enhancing robotic flexibility and resilience. It also explores converting tactile data back into visualizations, aiding manipulation of partially visible objects. The research aims to unlock new use cases in automated manufacturing and human-machine interaction, prioritizing safety and interpretability in critical environments.
Congrats to everyone involved!
18.11.2024
Related

©LMU/Stephan Höck
23.07.2025
Philipp Wicke Explores Embodied AI
MCML Junior Member Philipp Wicke explores how embodiment shapes intelligence in a new LMU research film on the role of the body in AI.

©LC Productions/LMU
26.06.2025
Every Household Needs a “Digital Chimney Sweep”– Insights From Johannes Kinder
MCML Associate Johannes Kinder highlights the security risks of smart devices in homes, emphasizing the need for regular updates and user awareness.

©Florian Generotzky / LMU
01.04.2025
AI as Co-Pilot
AI tools by Stefan Feuerriegel’s team at LMU support public decision-making, aiming for efficiency, transparency, and human control.

©Astrid Eckert / TUM
31.03.2025
Robot Jack Navigates Like a Human – A Project Led by Angela Schoellig
Angela Schoellig’s team at TUM developed robot Jack, which navigates safely through crowds using human-inspired motion planning.