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
Official implementation of the NeurIPS 2021 paper "Panoptic 3D Scene Reconstruction from a Single RGB Image"
Contributions:46 commits, 1 PR, 27 pushes in 11 months
pytorchreconstructionpython3d-scenepanoptic
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.
Request Free Trial
Manuel Dahnert - Machine Learning Engineer at NavVis