Richard Townsend
Waterloo, Ontario, Canada
Summary
🤩
RockstarRichard Townsend is a software developer with 12 years of experience focused on web-browser runtimes and Android, currently working on Chrome for Android at Google. He progressed through engineering and leadership roles at Arm, where he drove Chromium and Electron support for Windows on Arm and led the rollout of Armv9 security features like MTE, PAC and BTI. A Chromium committer with deep systems and embedded roots, he blends low-level platform work (UEFI, virtualization, ART) with large-scale browser engineering. Richard is also an active open-source contributor and machine-learning practitioner—his Go ML work added new data structures, discretisation and a random forest framework to a popular Go library. Based in Ontario, Canada, he pairs rigorous MEng training from the University of Warwick with hands-on experience shipping secure, high-performance browser platforms. Colleagues describe him as an engineer who moves fluidly between hardware-aware security features and higher-level NLP/browser problems.
12 years of coding experience
Github Skills (9)
algorithm10
decision-tree10
machine-learning10
machine-learning-algorithms10
go10
data-structure9
random-forest9
data-structures9
algorithms9
Programming languages (8)
Github contributions (5)
sjwhitworth/golearn
May 2014 - Dec 2022
Machine Learning for Go
Role in this project:
ML Engineer
ML EngineerContributions:6 reviews, 190 commits, 87 PRs in 8 years 9 months
Contributions summary:Richard implemented a new `Instances` and `Attribute` type for the project, refactoring existing code to use these new structures within the KNN classifier. They introduced a chi-merge filter and used it for discretisation. The user also worked on the ID3 algorithm, including the information gain rule generator, and created the basic framework of a random forest implementation.
gomachine-learning
Sentimentron/Dracula
Jun 2015 - Mar 2017
A deep, LSTM-based part of speech tagger and sentiment analyser using character embeddings instead of words. Compatible with Theano and TensorFlow. Optimized for Twitter.
Contributions:298 commits, 42 pushes, 17 branches in 1 year 8 months
lstmpart-of-speech-taggersentimenttensorflowtheano
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