Roger Labbe
Principal Engineer, Research And Development Special Projects at Sportvision
Mountain View, California, United States
Summary
🤩
Rockstar🎓
Top SchoolRoger Labbe is a Principal Engineer specializing in research and development of tracking, navigation, mapping, avionics, and real-time 2D/3D graphics with 12+ years of delivering production systems on time and on budget. He leads cross-disciplinary teams to design and ship robust computer vision, SLAM, and optimal-estimation solutions—most notably a multinocular system that achieves sub-foot tracking accuracy in highly adverse real-world conditions. Author and maintainer of the widely used filterpy library and the companion book on Kalman and Bayesian filtering, he blends deep theoretical expertise with pragmatic engineering across embedded, desktop, and cloud-connected platforms. His career includes inventing and commercializing avionics and augmented-reality products sold to government and industry customers, showing a knack for identifying markets and driving products from prototype to deployment. Based in Mountain View, he often enters unfamiliar domains (e.g., particle filtering, augmented reality) and rapidly produces high-leverage results, pairing mathematical rigor with hands-on system integration.
12 years of coding experience
23 years of employment as a software developer
BS, Computer Science, BS, Computer Science at Clarkson University
Stackoverflow
101reputation
0reached
0answers
0questions
Github Skills (4)
kalman-filter10
numpy10
python10
scipy9
Programming languages (5)
Github contributions (5)
rlabbe/filterpy
Jul 2014 - Aug 2022
Python Kalman filtering and optimal estimation library. Implements Kalman filter, particle filter, Extended Kalman filter, Unscented Kalman filter, g-h (alpha-beta), least squares, H Infinity, smoothers, and more. Has companion book 'Kalman and Bayesian Filters in Python'.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:1 release, 525 commits, 54 PRs in 8 years 2 months
Contributions summary:Roger primarily contributed to the development of a Kalman filtering and optimal estimation library using Python. Their work involved adding and modifying code related to Kalman filters, Extended Kalman filters, and various smoothing techniques. The user also implemented batch processing capabilities and added a Rauch-Tung-Striebel (RTS) smoother, demonstrating a focus on core filtering algorithms and their mathematical implementations. They were also responsible for the maintenance of core classes and methods.
pythonparticle-filterextended-kalman-filterleast-squaresbayesian
kod3r/Kalman-and-Bayesian-Filters-in-Python
May 2014 - Mar 2015
Contributions:393 commits in 9 months
pythonmathematicaltakestextbookipython-notebook
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