Manuel Dahnert is a machine learning engineer in Munich with nine years of experience bridging academic research and production ML, now building ML systems at NavVis after a PhD in Visual Computing at TUM. His research produced high-impact work on 3D scene understanding and CAD–scan alignment (CVPR/ICCV/NeurIPS) and he taught large-scale deep learning courses reaching thousands of students. Comfortable across geometry, vision and generative 3D methods, he combines rigorous publication-level research with practical engineering for real-world spatial perception products. A Stanford research visit and an interdisciplinary background in games engineering and interaction design give him an unusual blend of geometric rigor and user-centered thinking.
9 years of coding experience
2 years of employment as a software developer
Doctor of Philosophy - PhD Visual Computing, Doctor of Philosophy - PhD Visual Computing at Technical University of Munich
Erasmus year Interaction Design & Technology Software Engineering, Erasmus year Interaction Design & Technology Software Engineering at Chalmers University of Technology
Research Visitor Computer Science Geometric Computing Group, Research Visitor Computer Science Geometric Computing Group at Stanford University
[ICCV'19] Joint Embedding of 3D Scan and CAD Objects
Contributions:13 commits, 1 PR, 3 pushes in 1 year 10 months
3dcad
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