George Oastler
Software Engineer at Prosopo
West Suffolk, England, United Kingdom
Summary
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Rockstar🎓
Top SchoolGeorge Oastler is a software engineer based in West Suffolk with eight years’ experience building full-stack applications, embedded networks, and ML-driven solutions. He primarily develops in Java but is fluent in Python, JavaScript, C++ and Bash, and routinely applies SQL, APIs and CI/CD to ship reliable software. His work spans research and production — from contributing a Proximity Forest time-series classifier to the sktime project at the Alan Turing Institute to building containerised web apps and React/React Native mobile apps for university and public-sector clients. At Prosopo he is applying distributed infrastructure and smart contracts on Polkadot to real-world human verification problems, while also running small-business and accessibility-focused sites he designed himself. A pragmatic SCRUM coach and tutor, he combines teaching and team leadership with hands-on engineering, and in his spare time documents projects on his blog and explores machine learning and cycling.
8 years of coding experience
7 years of employment as a software developer
Engineering Diploma, Engineering Diploma at West Suffolk CollegeGCSE, GCSE at Stowupland High SchoolBachelor of Science - BSc, Computer Science, First, Bachelor of Science - BSc, Computer Science, First at University of East Anglia
Stackoverflow
272reputation
29kreached
4answers
10questions
Github Skills (20)
python10
classification10
scikit10
machine-learning10
time-series10
scikit-learn10
data-analysis10
data-structures8
data-structure8
algorithms8
algorithm8
testing7
typescript-eslint6
lodash6
android6
Programming languages (10)
Github contributions (5)
sktime/sktime
Apr 2019 - Jan 2021
A unified framework for machine learning with time series
Role in this project:
ML Engineer
ML EngineerContributions:86 commits, 17 PRs, 96 pushes in 1 year 10 months
Contributions summary:George's commits focus on the development and implementation of a Proximity Forest classifier within the sktime repository. Their contributions include the creation of the ProximityForest, ProximityTree, and ProximityStump classes, along with the integration of distance measures and parameter configurations. They also worked on test implementations and debugging, indicating a focus on building and validating time series classification models.
forecastingtime-series-analysistime-series-regressiondata-sciencedeep-learning
time-series-machine-learning/tsml-java
Dec 2018 - May 2021
Java time series machine learning tools in a Weka compatible toolkit
Contributions:1222 commits, 49 PRs, 358 pushes in 2 years 5 months
machine-learningtime-seriesjavawekajava-time
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