Boyd Kane is an embedded software engineer and research fellow with eight years of experience applying machine learning and control systems to real-world robotics and aerospace problems. Based in Berkeley, he currently develops satellite attitude-control software at CubeSpace ADCS and conducts applied research at MATS Research, blending hands-on embedded development with academic rigor from a rapid nine-month MSc thesis on gesture-based typing. His background includes impactful tooling work at AWS and technical writing contributions to TensorFlow docs, showing a knack for clarifying complex systems and streamlining examples. Comfortable across low-level firmware, control algorithms, and ML pipelines, he prefers hardware- and systems-oriented roles over web stacks and brings a proven ability to take ownership of end-to-end solutions.
8 years of coding experience
1 year of employment as a software developer
Bachelor of Science - BS Computer Science and Mathematical Statistics, Bachelor of Science - BS Computer Science and Mathematical Statistics at University of Cape Town
Contributions summary:Boyd primarily contributed to the TensorFlow documentation repository by fixing errors and improving existing content. They corrected dead links and typos within the documentation, and also made changes to the autoencoder tutorial. Their work streamlined the code example in the tutorial and updated code style.
Got a cardgame idea? This project will convert it to printable PDFs which you can cut out!
Contributions:1 release, 1 review, 71 commits in 1 year
pdfcardgamecutpdfsprintable
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