Research Blog
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 …
09.10.2025
Rethinking AI in Public Institutions - Balancing Prediction and Capacity
Researcher in Focus: Unai Fischer Abaigar
Unai Fischer Abaigar is a researcher at MCML whose work focuses on improving decision-making in public institutions by developing AI systems that are both fair and effective in practice.
29.09.2025
Machine Learning for Climate Action - With Researcher Kerstin Forster
Research Film
How can machine learning fight climate change? Kerstin Forster, researcher at LMU and MCML, explores how AI can help reduce greenhouse gas emissions, improve renewable energy systems, and enhance early warning for extreme weather.
26.09.2025
Making Machine Learning More Accessible With AutoML
Researcher in Focus: Matthias Feurer
Matthias Feurer is a Thomas Bayes Fellow and interim professor, funded by the MCML and a member of the Chair of Statistical Learning and Data Science at LMU. He aims to simplify the usage of machine learning by researching methods and developing tools that allow the usage of machine learning by domain scientists and also make machine learning more …
25.09.2025
Compress Then Explain: Faster, Steadier AI Explanations - With One Tiny Step
MCML Research Insight - With Giuseppe Casalicchio and Bernd Bischl
Imagine re-running feature importance plots and getting slightly different “top features.” Annoying, right? That uncertainty often comes from a quiet assumption: model explanation algorithms typically sample points from data at random. A new ICLR 2025 Spotlight paper by MCML Junior Member Giuseppe Casalicchio, MCML Director Bernd Bischl, first …
22.09.2025
Predicting Health With AI - With Researcher Simon Schallmoser
Research Film
How can AI predict medical conditions and personalize treatments? Simon Schallmoser, researcher at LMU and MCML, uses machine learning to forecast health risks and optimize care for patients based on their individual profiles.
18.09.2025
GCE-Pose – Predicting Whole Objects From Partial Views
MCML Research Insight - With Weihang Li, Junwen Huang, Hyunjun Jung, Nassir Navab, and Benjamin Busam
Imagine trying to identify the full shape of a familiar object, e.g. a mug, when only its handle is visible. That’s the challenge a computer faces when estimating the pose of an object (its orientation and size) from partial data. GCE‑Pose, a new approach from MCML Junior Members Weihang Li, Junwen Huang, Hyunjun Jung, Benjamin Busam, MCML PI …
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17.09.2025
Research Stay at Harvard University
Hannah Laus – Funded by the MCML AI X-Change Program
This summer, I had the incredible opportunity to spend 11 weeks at Harvard University as part of the AI X-change program, visiting the group of Flavio Calmon at the Harvard John A. Paulson School of Engineering and Applied Sciences. The idea for this visit came after my former office mate and collaborator, Claudio Mayrink Verdun, a former member of …
15.09.2025
Robots Seeing in the Dark - With Researcher Yannick Burkhardt
Research Film
What if robots could see in the dark and react faster than any human? Yannick Burkhardt, researcher at TUM and MCML, researches event cameras that capture motion in a revolutionary way. Unlike traditional cameras that take full pictures at fixed intervals, event cameras detect every tiny change in light—up to a million times per second—and feed …
08.09.2025
3D Machine Perception Beyond Vision - With Researcher Riccardo Marin
Research Film
Can AI understand the world in 3D the way we do? Riccardo Marin, researcher at TUM and MCML, works at the intersection of computer vision and 3D geometry to teach machines how to perceive shapes, patterns, and spatial structures. His work ranges from detecting production flaws in manufacturing to analyzing archaeological artifacts – showing how …
01.09.2025
AI for Personalized Psychiatry - With Researcher Clara Vetter
Research Film
Can AI help us understand why some people develop mental disorders while others remain resilient? MCML Junior Member Clara Vetter, PhD candidate in the group of our Director Daniel Rückert, uses machine learning to uncover hidden patterns in brain scans, genetic data, and even smartphone-based information. Her goal: identifying biological markers …
25.08.2025
Satellite Insights for a Sustainable Future - With Researcher Ivica Obadic
Research Film
Can AI from satellite imagery help us design more liveable cities, improve well-being, and ensure sustainable food production? Ivica Obadić, PhD student in the group of our PI Xiaoxiang Zhu, and MCML, develops transparent AI models that not only predict change but also give actionable insights for urban planners.
18.08.2025
Digital Twins for Surgery - With Researcher Azade Farshad
Research Film
Azade Farshad, MCML Junior Member and PhD student in the research group of Nassir Navab, researches digital twins of patients at TUM and MCML to improve personalized treatment, surgical planning, and training. Using graph-based analysis and multimodal patient data, she builds models that create realistic surgical simulations — helping surgeons …
13.08.2025
From Physics Dreams to Algorithm Discovery - With Niki Kilbertus
Research Film
As a kid, Niki Kilbertus dreamed of becoming a theoretical physicist and discovering a fundamental law of nature. But when reality proved more complex, he found a new path through computer science.
12.08.2025
Tracking Actions in Space and Time: ICCV 2025 Challenge & Workshop
MCML Research Insight - With Tanveer Hannan, Mark Weber, and Thomas Seidl
Tracking actions, not just objects: The Spatiotemporal Action Grounding Challenge and Workshop at ICCV 2025 focusses on detecting and localizing actions both in space and time within complex, real-world videos. Unlike standard action recognition, this task requires identifying when and where an action occurs, pushing models to handle long, diverse, …
11.08.2025
AI for Dynamic Urban Mapping - With Researcher Shanshan Bai
Research Film
Imagine using social media to build a “living map” of our cities. Meet Shanshan Bai, MCML junior member and PhD student PhD student in the group of our PI Xiaoxiang Zhu, who’s decoding the world around us with geo-tagged social media data.
07.08.2025
Precise and Subject-Specific Attribute Control in AI Image Generation
MCML Research Insight - With Felix Krause, Vincent Tao Hu, and Björn Ommer
Text-to-image (T2I) models like Stable Diffusion have become masters at turning prompts like “a happy man and a red car” into vivid, detailed images. But what if you want the man to look just a little older, or the car to appear slightly more luxurious without changing anything else? Until now, that level of subtle, subject-specific control was …
06.08.2025
What Is Intelligence—and What Kind of Intelligence Do We Want in Our Future? With Sven Nyholm
Research Film
Sven Nyholm, Chair of the Ethics of AI at LMU Munich and PI at MCML, explores one of the most urgent questions in AI: how responsibility, agency, and credit shift when intelligent systems make decisions for us.
04.08.2025
AI for Better Social Media - With Researcher Dominik Bär
Research Film
Meet Dominik Bär, MCML junior member and PhD student at LMU exploring how AI can enhance the integrity of social media platforms. Dominik’s work goes beyond just detecting harmful content like hate speech and misinformation. He’s developing AI that understands why content is posted and generates thoughtful, human-like responses - so-called …
31.07.2025
From Vulnerable to Verified: Exact Certificates Shield Models From Label‑Flipping
MCML Research Insight - With Lukas Gosch, Stephan Günnemann and Debarghya Ghoshdastidar
Machine‑learning models can be undermined before training even starts. By silently altering a small share of training labels - marking “spam” as “not‑spam,” for instance - an attacker can cut accuracy by double‑digit percentages. The paper “Exact Certification of (Graph) Neural Networks Against Label Poisoning” by MCML Junior Member Lukas Gosch, …
30.07.2025
Tracking Our Changing Planet From Space - With Xiaoxiang Zhu
Research Film
From dreaming of seeing the Earth from space to leading efforts to understand our planet using AI and satellite data to tackle urgent global challenges. Xiaoxiang Zhu, Chair Professor for Data Science in Earth Observation at TUM and PI at MCML, develops machine learning systems that analyze petabytes of satellite imagery. Her work focuses on …