29.09.2025
Machine Learning for Climate Action - With Researcher Kerstin Forster
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
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 …
25.09.2025
Compress Then Explain: Faster, Steadier AI Explanations - With One Tiny Step
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 …
22.09.2025
Predicting Health With AI - With Researcher Simon Schallmoser
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
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 …
17.09.2025
Research Stay at Harvard University
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 …
15.09.2025
Robots Seeing in the Dark - With Researcher Yannick Burkhardt
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 …
08.09.2025
3D Machine Perception Beyond Vision - With Researcher Riccardo Marin
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 …
01.09.2025
AI for Personalized Psychiatry - With Researcher Clara Vetter
Can AI help us understand why some people develop mental disorders while others remain resilient? Clara Vetter, PhD candidate at LMU and MCML, uses machine learning to uncover hidden patterns in brain scans, genetic data, and even smartphone-based …
25.08.2025
Satellite Insights for a Sustainable Future - With Researcher Ivica Obadic
Can AI from satellite imagery help us design more liveable cities, improve well-being, and ensure sustainable food production? Ivica Obadić, PhD student at TUM and MCML, develops transparent AI models that not only predict change but also give …
18.08.2025
Digital Twins for Surgery - With Researcher Azade Farshad
Azade Farshad 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 …
13.08.2025
From Physics Dreams to Algorithm Discovery - With Niki Kilbertus
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
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 …
07.08.2025
Precise and Subject-Specific Attribute Control in AI Image Generation
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 …
06.08.2025
What Is Intelligence—and What Kind of Intelligence Do We Want in Our Future? With Sven Nyholm
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
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 …
31.07.2025
From Vulnerable to Verified: Exact Certificates Shield Models From Label‑Flipping
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 …
30.07.2025
Tracking Our Changing Planet From Space - With Xiaoxiang Zhu
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, …
29.07.2025
AI for Enhanced Eye Diagnostics - With Researcher Lucie Huang
Curious how AI is revolutionizing the treatment of eye diseases? Learn more about what AI can do for ophthalmology with Lucie Huang, MCML junior member and PhD student at TUM, who is developing AI for sharper and faster eye scans. This means earlier …
24.07.2025
SceneDINO: How AI Learns to See and Understand Images in 3D–Without Human Labels
Imagine looking at a single image and trying to understand the entire 3D scenery–not just what’s visible, but also what’s occluded. Humans do this effortlessly: when we see a photo of a tree, we intuitively grasp its 3D structure and semantic …
23.07.2025
How Reliable Are Machine Learning Methods? With Anne-Laure Boulesteix and Milena Wünsch
Often a new machine learning method claims to outperform the last. Whether it’s in bioinformatics, finance, or image recognition, the message is the same: this algorithm is faster, more accurate, more powerful. But can we trust those claims?
16.07.2025
AI-Powered Cortical Mapping for Neurodegenerative Disease Diagnoses - With Christian Wachinger
Christian Wachinger, Professor of AI in Radiology at the Technical University of Munich and PI at MCML, is developing AI systems to precisely reconstruct the brain’s cortex — an extremely thin and highly folded sheet of neural tissue — in order to …
10.07.2025
Capturing Complexity in Surgical Environments
Imagine an operating room - a space filled with intricate interactions, rapid decisions, and precise movements. Now, imagine capturing every detail of such a complex environment not just visually but also through sound, dialogue, robot movements, and …
10.07.2025
Beyond Prediction: How Causal AI Enables Better Decision-Making - With Stefan Feuerriegel
A good prediction is rarely a good decision. This may sound surprising in an age where AI is often celebrated for its predictive power. But when it comes to making real-world decisions — especially in complex environments like business or healthcare …
07.07.2025
How Neural Networks Are Changing Medical Imaging – With Reinhard Heckel
Clear imaging is essential for accurate diagnosis — but when it comes to the heart, motion makes it one of the most difficult organs to capture in high resolution. Traditional reconstruction methods often struggle to deliver the detail clinicians …
26.06.2025
What Words Reveal: Analyzing Language in the Trump–Harris 2024 Debate
In presidential debates, every word counts - not only what candidates say but how they say it. Words are carefully selected to resonate with voters’ values, fears, and hopes. A new insightful study by MCML Junior Member Philipp Wicke and Marianna M. …
25.06.2025
When Clinical Expertise Meets AI Innovation – With Michael Ingrisch
Artificial intelligence has enormous potential in radiology — but realizing it requires more than good algorithms. Michael Ingrisch, Clinical Data Science Professor at LMU and MCML PI, shares how his team took a practical approach: identifying a key …
23.06.2025
Autonomous Driving: From Infinite Possibilities to Safe Decisions— With Matthias Althoff
How can we guarantee that autonomous vehicles always make the right decision in unpredictable traffic?
Matthias Althoff, Professor at the chair of Cyber-Physical Systems at the Technical University of Munich and MCML PI, explores the complex challenge …
20.06.2025
Zooming in on Moments: ReVisionLLM for Long-Form Video Understanding
Imagine watching a two-hour video and trying to find the exact moment someone scores a goal - or says something important. Humans can do this with ease by skimming and zooming in. But for AI, finding specific moments in long videos is incredibly …
11.06.2025
Better Data, Smarter AI: Why Quality Matters – With Frauke Kreuter
How does data quality shape the future of AI? Frauke Kreuter, Professor at the Chair of Statistics and Data Science at LMU Munich and MCML PI, shares her insights on the fundamental role of data quality in the development and deployment of AI.
30.04.2025
Who Spreads Hate?
Hate speech on social media isn’t just offensive - it’s dangerous. It spreads quickly, harms mental health, and can even contribute to real-world violence. While many studies have focused on identifying hate speech or profiling those who create it, a …
29.04.2025
How Certain Is AI? an Introduction to Bayesian Deep Learning
MCML Junior Member Emanuel Sommer is a PhD-student at the Munich Uncertainty Quantification AI Lab at LMU Munich supervised by David Rügamer. His research focuses on Scalable and Reliable (Bayesian) Deep Learning.
10.04.2025
Text2Loc: A Smarter Way to Navigate With Words
Imagine standing in an unfamiliar part of a city, no GPS in sight. All you can say is, “I’m west of a green building, near a black garage.” That might be vague to a machine, but Text2Loc understands you perfectly. With this powerful new system, AI …
03.04.2025
CUPS: Teaching AI to Understand Scenes Without Human Labels
Understanding the location and semantics of objects in a scene is a significant task, enabling robots to navigate through complex environments or facilitating autonomous driving. Recent AI models for understanding scenes from images require …
27.03.2025
Beyond the Black Box: Choosing the Right Feature Importance Method
Machine learning models make powerful predictions, but can we really trust them if we don’t understand how they work? Global feature importance methods help us discover which factors really matter - but choosing the wrong method can lead to …
13.03.2025
ReNO: A Smarter Way to Enhance AI-Generated Images
Despite their impressive capabilities, Text-to-Image (T2I) models frequently misinterpret detailed prompts, leading to errors in object positioning, attribute accuracy, and color fidelity. Traditional improvements rely on extensive dataset training, …
04.03.2025
Research at EWCS at the Broad Institute of MIT and Harvard
During my research stay at Broad Institute of MIT and Harvard in autumn 2024, I had the pleasure of being part of the research group led by Caroline Uhler, Director of the Eric and Wendy Schmidt Center (EWCS) at the Broad Institute, and Andrew (1956) …
27.02.2025
ChatGPT in Radiology: Making Medical Reports Patient-Friendly?
Medical reports, especially in radiology, are commonly difficult for patients to understand. Filled with complex terminology and specialized jargon, these reports are primarily written for medical professionals, often leaving patients struggling to …
11.02.2025
Can AI Help Solve Complex Physics Equations? Meet APEBench
Our Junior Member Felix Köhler, together with our PIs Rüdiger Westermann and Nils Thuerey, and collaborator Simon Niedermayr, have introduced APEBench, an innovative benchmark suite. APEBench sets a new standard for evaluating autoregressive neural …
06.02.2025
Improving Business Processes
MCML Junior Member Gabriel Marques Tavares has a PostDoc position at the chair of Database Systems and Data Mining at LMU Munich. His research focus is in the field of Process Mining, which investigates the execution of business processes within …
15.01.2025
TruthQuest – A New Benchmark for AI Reasoning
In their recent work, “Liar, Liar, Logical Mire: A Benchmark for Suppositional Reasoning in Large Language Models” our Junior Member Philipp Mondorf and our PI Barbara Plank tackle a fascinating question: How well do AI systems handle complex …
07.01.2025
Research Collaboration Between TUM/MCML and Stanford University
During the summer of 2024, I had the privilege of representing the Computer Vision Group at TUM, led by Prof. Daniel Cremers, in a collaborative research project with the Geometric Computing Group at Stanford University, headed by Prof. Leonidas …
19.12.2024
Epistemic Foundations and Limitations of Statistics and Science
The Open Science Initiative in Statistics - which is part of the Open Science Center at LMU Munich - and MCML recently hosted a workshop about epistemic foundations and limitations of statistics and science. The event brought together researchers …
11.12.2024
Understanding Vision Loss and the Need for Early Treatment
MCML Junior Member Jesse Grootjen is writing his doctoral thesis at the Chair of Human-Centered Ubiquitous Media at LMU Munich. The group conducts research at the crossroads of human computer interaction, media technology, and ubiquitous computing. …
28.11.2024
Enhancing the Integrity of Social Media With AI
MCML Member Dominik Bär is a researcher at the Institute of Artificial Intelligence (AI) in Management at LMU, working within the research group of Stefan Feuerriegel. He is pursuing his PhD with a focus on social media analytics.
12.11.2024
Exploring the Impact of AI in Medicine
MCML Junior Member Anna Reithmeir is writing her doctoral thesis at the Chair of “Computational Imaging and AI in Medicine” at TUM. Her work addresses the complexity of aligning images from different times or modalities, enabling the comparison of …
08.04.2024
Get to Know MCML Junior Member Lukas Gosch
MCML Junior Member Lukas Gosch conducts research on how quickly - or slowly - AI algorithms react to changes. His field of work is the reliability of artificial intelligence, or more precisely, of machine learning algorithms. As these algorithms are …
02.04.2024
Get to Know MCML Junior Member Maximiliane Windl
MCML Junior Member Maximiliane Windl’s research focuses on understanding and mitigating privacy concerns in ubiquitous computing systems. Her main concern is one thing: how can people become more aware of what data these devices are constantly …
18.03.2024
Get to Know MCML Junior Member Lisa Wimmer
MCML Junior Member Lisa Wimmer researches the practicability of model predictions. By supplementing them with a reliable statement about their statistical certainty or uncertainty, she aims for improving the underlying models.
11.03.2024
Get to Know MCML Junior Member Martin Binder
Artificial intelligence only becomes a disadvantage if it is overestimated or used incorrectly, says MCML Junior Member Martin Binder. In his research, he improves algorithms and, above all, simplifies the work of other scientists.
04.03.2024
Get to Know MCML Junior Member Moritz Herrmann
MCML Junior Member Moritz Herrmann conducts research at LMU at the Institute for Medical Information Processing, Biometry and Epidemiology. He compares methods of AI and ML that could predict the survival time of cancer patients. Besides his …
26.02.2024
Get to Know MCML Junior Member Clara Sophie Vetter
In her research, MCML Junior Member Clara Sophie Vetter wants to find out how depression and psychosis are linked - with the help of artificial intelligence. In the “Precision Psychiatry” working group at LMU Hospital, she is investigating how the …
19.02.2024
Get to Know MCML Junior Member Valentin Hofmann
Valentin Hofmann is actually a former MCML Junior Member. He was a researcher at LMU and a PHD student at the University of Oxford and recently finished his PhD. He is now a Young Investigator (Postdoc) at the Allen Institute for AI. During his PhD, …
13.02.2024
Get to Know MCML Junior Member Julian Rasch
Julian Rasch is an electrical engineer and computer science PhD. He is conducting research about the interaction of humans and machines in virtual space. His current work is about how to better communicate virtual movement intentions.