Zan Gojcic
Director Of Research at NVIDIA
Zurich, Zurich, Switzerland
Summary
👤
Senior🎓
Top SchoolZan Gojcic is a Director of Research at NVIDIA with eight years of experience translating academic rigor into impactful machine learning solutions for point cloud processing. Trained at ETH Zürich (PhD) and a former visiting researcher at Stanford, he has advanced research in registration, feature extraction, scene flow, and domain adaptation—particularly for autonomous driving. At NVIDIA he progressed rapidly from research scientist to director, leading teams that bridge weakly/unsupervised learning research with production-relevant systems. His background in geomatics and hands-on work with GNSS and geodetic systems gives him a practical edge in spatial reasoning and real-world sensor challenges. Colleagues know him for turning complex 3D problems into elegant learning-based approaches that scale beyond lab settings.
8 years of coding experience
5 years of employment as a software developer
Master’s Degree, Geomatics science - Engineering Geodesy, Master’s Degree, Geomatics science - Engineering Geodesy at Technische Universität GrazBachelor’s Degree, Geodesy and Geoinformation, Bachelor’s Degree, Geodesy and Geoinformation at University of Ljubljana, Faculty of Civil and Geodetic EngineeringDruga gimnazija MariborDoctor of Philosophy - PhD, Doctor of Philosophy - PhD at ETH ZürichVisiting Researcher, Computer Science, Visiting Researcher, Computer Science at Stanford University
German, English, Slovenian
Github Skills (69)
attention-mechanism10
convolutional-neural-networks10
perfect10
correspondence10
neural-rendering10
scene10
poisson10
matching10
weakly-supervised-learning10
descriptor10
sampling9
3d-reconstruction9
computer-vision9
overlap9
sparse9
Programming languages (6)
Github contributions (5)
zgojcic/zgojcic.github.io
Nov 2019 - Mar 2025
Personal webpage
Contributions:2 PRs, 107 pushes, 1 branch in 5 years 4 months
reactpersonal-webpagewebpage
zgojcic/3DSmoothNet
Mar 2019 - Nov 2021
[CVPR2019] The Perfect Match: 3D Point Cloud Matching with Smoothed Densities
Contributions:12 commits, 1 PR, 10 pushes in 2 years 8 months
pointcloudmatchingcomputer-visionneural-renderingperfect
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