Rufus Behr
Research Software Engineer at Northeastern University
United States
Summary
👤
Senior🎓
Top SchoolRufus Behr is a research software engineer with a strong foundation in computing science and mathematics and roughly a decade of hands-on experience across academia and industry. He blends applied machine learning, full-stack development, and systems deployment—having improved radiotelemetry localization errors, built production document-classification and CNN models for insurance automation, and delivered front-end and back-end features at Goldman Sachs with 100% Jest test coverage. Comfortable moving between research and production, he has led academic projects exploring ML-driven chess modeling and shipped services on AWS Lambda and ECS Fargate. An avid problem solver and linguistics enthusiast, Rufus brings curiosity-driven rigor to complex engineering problems and a track record of turning research prototypes into reliable, deployable systems.
10 years of coding experience
3 years of employment as a software developer
Non Matriculated Student, 4.0, Non Matriculated Student, 4.0 at Concordia College-New YorkBachelor of Science - BSc, Computing Science and Mathematics, First Class, Bachelor of Science - BSc, Computing Science and Mathematics, First Class at University of AberdeenNon-Matriculated Student, 4.0, Non-Matriculated Student, 4.0 at Westchester Community CollegeHigh School Diploma, High School Diploma at Fordham Preparatory SchoolBachelor of Science - BS, Computer Engineering, Bachelor of Science - BS, Computer Engineering at Rensselaer Polytechnic Institute
Latin, Greek, Chinese, English, elvish sindarin
Github Skills (30)
sandbox9
java9
terasology9
voxel9
voxel-engine8
stat7
game-development7
hubot6
game-engine6
azerothcore5
gift5
quality-assurance5
sarif5
test-data4
thunderbird4
Programming languages (5)
Github contributions (5)
SufurElite/sufurelite.github.io
Mar 2017 - Aug 2019
Contributions:19 pushes, 1 branch in 2 years 6 months
SufurElite/ML-Telemetery-Error-Localisation-Reduction
Jul 2022 - Mar 2023
A repository worked on and developed as a consequence of the Quadrat summer research program with the University of Aberdeen to use machine learning to reduce localisation errors in automated telemetry systems
Contributions:1 review, 12 PRs, 41 pushes in 8 months
machine-learningtelemetrysummerlocalisationaberdeen
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