18.09.2025
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 …
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17.09.2025
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 …
15.09.2025
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 …
08.09.2025
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
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 information. Her goal: identifying biological markers that could improve diagnosis and treatment in …
25.08.2025
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 actionable insights for urban planners.