Mark Canning
Software Engineer at Google
Sunnyvale, California, United States
Summary
👤
Senior🎓
Top SchoolMark Canning is a software engineer with 14 years of technical experience and a BS in Physics and Mathematics from UC Berkeley, currently focused on engineering productivity research at Google since 2019. He blends data ingestion and analysis with user research to design studies, surveys, and metrics that improve developer productivity and satisfaction. Previously he built routing protocols and customer-facing CLIs at Arista, pairing low-level networking work with direct customer debugging. An active open-source contributor, he optimized statistical distributions in the widely used gonum numeric library—improving random number generation performance and edge-case accuracy for Gamma and Poisson samplers. Based in Sunnyvale, he brings a quantitative, physics-informed approach to shipping reliable, performance-sensitive systems.
14 years of coding experience
3 years of employment as a software developer
Bachelor of Science (BS), Physics and Mathematics, GPA: 3.212, Bachelor of Science (BS), Physics and Mathematics, GPA: 3.212 at University of California, Berkeley
Github Skills (18)
algorithm10
algorithms10
performance-analytics10
performance-monitor10
statistics10
data-structure10
performance-measurement10
go10
performance-analysis10
performance-tuning10
data-structures10
performance-monitoring10
scientific-computing10
data-analysis10
matrix9
Programming languages (3)
Github contributions (5)
gonum/gonum
Sep 2020 - Sep 2021
Gonum is a set of numeric libraries for the Go programming language. It contains libraries for matrices, statistics, optimization, and more
Role in this project:
Back-end Developer
Back-end DeveloperContributions:2 reviews, 5 commits, 7 PRs in 1 year
Contributions summary:Mark focused on optimizing the performance of the `gonum/gonum` library, specifically within its statistical distributions. Their commits improved the speed of random number generation for Gamma and Poisson distributions, including addressing edge cases and implementing specialized algorithms for different parameter ranges. The changes included benchmark testing to quantify the performance gains. They also corrected documentation and made adjustments to the Pareto distribution.
golangdata-analysisstatisticsmatricesoptimization
argusdusty/MaxPianoSynth
Dec 2013 - Sep 2021
Contributions:6 commits, 2 pushes in 7 years 9 months
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