Matthew Self
Principal Engineer at GE HealthCare
Redwood City, California, United States
Summary
👤
Senior🎓
Top SchoolMatthew Self is a Principal Engineer with over three decades of technical and leadership experience and a decade specifically in senior engineering roles, currently integrating AI-driven ultrasound technology at GE HealthCare after leading Caption Health through acquisition. He has built foundational products across startups and large firms—from the first consumer DVR and early NeXT development tools to Box Drive and mobile VoIP—combining product vision with hands-on systems and performance engineering. An active contributor to OpenCV, he has optimized core computer vision routines for determinism and SIMD performance, highlighting deep expertise in algorithmic optimization. Known for shipping commercially transformative platforms and guiding teams through acquisition and IPO events, he blends research-level results (early SLAM and AI work) with pragmatic delivery. Based in Redwood City, he pairs a UC Berkeley physics background with a rare track record of moving cutting-edge research into widely used, production-grade software.
10 years of coding experience
32 years of employment as a software developer
BA Physics, BA Physics at University of California, Berkeley
Github Skills (6)
computer-vision10
opencv10
c-language10
cprogramming-language10
performance-optimization10
image-processing10
Programming languages (8)
Github contributions (5)
opencv/opencv
Jul 2016 - Aug 2016
Open Source Computer Vision Library
Role in this project:
Back-end Developer & Performance Engineer
Back-end Developer & Performance EngineerContributions:5 commits, 6 PRs, 58 comments in 1 month
Contributions summary:Matthew primarily contributed to improving the performance and efficiency of the OpenCV library. They addressed deterministic behavior in feature tracking algorithms and added support for capturing video frames using different modes. Furthermore, they optimized the median calculation within the LMedS algorithm by utilizing `nth_element`, resulting in significant performance improvements for specific functions, namely `EstimateAffine2D()`. The contributions also involved interleaved memory operations optimization for SIMD instructions.
pythonvisiondeep-learningc-plus-pluscomputer-vision
box/samples
Jan 2017 - May 2017
Code snippets and samples to demonstrate how to get the most out of the Box platform & API
Contributions:20 commits, 2 PRs, 20 pushes in 3 months
apiapi-platformboxout-of-the-boxsdk
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