Matthias Grundmann
Research Director at Google
San Jose, California, United States
Summary
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Senior🎓
Top SchoolMatthias Grundmann is a Research Director at Google Research with 12 years of experience building on-device, real-time computational video and GPU inference systems for mobile platforms. He leads work on perception and augmentation technologies—tracking, face perception, stabilization, segmentation, cinemagraphs and AR—that have shipped in products like YouTube Stories, Motion Stills, Google Photos, and Pixel features. A PhD-trained computer scientist, he bridges deep research and production engineering, turning advanced algorithms into optimized, low-latency mobile implementations. He also contributes to foundational open-source computer vision tooling, having fixed race conditions and performance issues in the widely used OpenCV library. Based in San Jose, he combines hands-on systems optimization with product-facing integrations, often solving subtle multi-threading and performance problems that are invisible to end users.
11 years of coding experience
Doctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at Georgia Institute of TechnologyBachelor's degree Mathematics and Computer Science, Bachelor's degree Mathematics and Computer Science at Technical University of Munich
Github Skills (13)
computer-vision10
opencv10
c-language10
cprogramming-language10
multithreading10
image-processing10
ffmpeg9
optimization9
optimisation9
numerical-optimization9
algorithm9
code-optimization9
algorithms9
Programming languages (3)
Github contributions (5)
opencv/opencv
Oct 2015 - May 2017
Open Source Computer Vision Library
Role in this project:
Software Engineer
Software EngineerContributions:12 commits, 12 PRs, 7 comments in 1 year 7 months
Contributions summary:Matthias primarily contributed to bug fixes, optimizations, and minor feature updates within the OpenCV library. Their work involved addressing race conditions in multithreading code, improving FPS calculation in video input, optimizing image resizing, and preventing potential division-by-zero errors in background subtraction algorithms. They also focused on code maintenance by fixing issues related to missing headers and whitespace, along with minor updates.
pythonvisiondeep-learningc-plus-pluscomputer-vision
videosegmentation/video_segment
Jun 2014 - Aug 2014
Main repository for The Video Segmentation Project
Contributions:32 commits, 2 comments in 1 month
video-segmentationcomputer-visionvideosegmentation
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