06.11.2025
Industry Pitch Talks Recap
With the Stadtwerke München (SWM)
On 4 November 2025, Stadtwerke München (SWM) welcomed representatives from the Munich Center for Machine Learning (MCML) for a focused session of Industry Pitchtalks. The event highlighted the growing synergy between academic research and real-world applications of artificial intelligence in energy, …
06.11.2025
AI, Ethics and Society Workshop
Short Recap
On 29 October 2025, the workshop “AI, Ethics and Society” brought together researchers and practitioners from the Junges Kolleg | BAdW, Munich Center for Machine Learning (MCML) and bidt – Graduate Center für Postdocs to explore how artificial-intelligence algorithms shape individual and collective …
©Gorodenkoff-stock.adobe.com
03.11.2025
Research on Human-Centred Exosuit Technology Highlighted in Börsen-Zeitung
MCML Research About Wearable Robotics
LMU and Harvard researchers outline a new approach to smarter and safer wearable technology. Their latest method not only optimizes complex decisions—like how an exosuit should assist a worker during heavy lifting—but also explains why those decisions are made. By making AI’s reasoning transparent …
©Terzo Algeri/Fotoatelier M/ TUM
30.10.2025
Language Shapes Gender Bias in AI Images
TUM News
Alexander Fraser, MCML PI, and his team discovered that AI image generators reproduce gender stereotypes differently across languages. In their study of nine languages, they found that generic prompts like “accountant” mostly produced male images, while explicitly feminine or neutral prompts reduced bias but sometimes affected image quality. The …
26.10.2025
Barbara Plank Featured on ARD
The Segment Highlights Challenges AI Faces in Understanding Regional Language Variations
MCML PI Barbara Plank was featured in a recent ARD Capriccio segment on how AI struggles to understand dialects. The broadcast highlighted research from the MaiNLP lab, with insights from Verena Blaschke, showcasing the challenges of applying AI language models to regional variations.
26.10.2025
Unai Fischer-Abaigar Featured on Executive Code
AI Prediction and Its Impact on Government Resource Allocation
MCML Junior Member Unai Fischer-Abaigar, was featured in a recent episode of Executive Code. He discussed his paper “The Value of Prediction in Identifying the Worst-Off”, exploring how governments use AI to allocate limited resources and when improving predictive models is more effective than simply expanding access to public programs. Using real …
24.10.2025
Digdeep Podcast: Live From HerCareer With Anne Greul: How to Successfully Pivot a Startup.
News From the Digital World by MCML PI Frauke Kreuter and Christof Horn
In the new episode of #digdeep, Anne Greul shows startup-pivots form herCareer. Anne took the courageous step into entrepreneurship and learned early on that the path is rarely straightforward. Instead of pursuing a classic career in consulting or the automotive industry, she founded a startup in the Web 3.0 and blockchain sector with partners – but …
20.10.2025
Björn Ommer Appointed LMU Chief AI Officer
LMU News
As of October 1, our PI Björn Ommer, has been appointed LMU’s Chief AI Officer. In his new role, he will help strengthen LMU’s strategic profile in Artificial Intelligence and further expand research and transfer activities in this key area – in close collaboration with TUM and non-university partners.
17.10.2025
Call for Applications: Data Science Professional Certificate Program @LMU 2026
Application Deadline: 16.01.2026
The Data Science Certificate Program at LMU Munich, offered in collaboration with MCML, is a graded, part-time academic training program. It is designed for working professionals, researchers, and executives who want to improve their skills in the field of data analytics, statistics, and machine learning. The program is offered twice a year. Apply …
16.10.2025
SIC: Making AI Image Classification Understandable
MCML Research Insight - With Tom Nuno Wolf, Emre Kavak, Fabian Bongratz, and Christian Wachinger
Deep learning models are emerging more and more in everyday life, going as far as assisting clinicians in their diagnosis. However, their black box nature prevents understanding errors and decision-making, which arguably are as important as high accuracy in decision-critical tasks. Previous research typically focused on either designing models to …