Justin Dujardin
Founder at DuJardin Consulting, LLC
Eugene, Oregon, United States
Summary
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RockstarJustin Dujardin is a founder and seasoned full-stack software engineer with 15 years of experience delivering tailored software solutions from Eugene, Oregon. He runs DuJardin Consulting, blending hands-on engineering with open source contributions that improve developer tooling and front-end UX—most notably refinements to widely used select libraries like Select2 and Chosen. His work spans UI, automation, testing, and machine learning, including ML curriculum and reward-balancing features in a project for step-by-step CAS problem solving. Justin has steered engineering teams as Chief Architect and Director of Engineering while also shipping build and CLI improvements for popular tooling such as Docco and strengthening deep-learning library test suites. Known for pragmatic code-level fixes that improve cross-browser and cross-platform compatibility, he combines entrepreneurial instinct with a focus on durable, user-friendly interfaces.
15 years of coding experience
9 years of employment as a software developer
Github Skills (28)
javascript10
jquery10
pytest10
python10
testing10
css10
command-line-interface10
machine-learning10
reinforcement-learning10
select210
tensorflow10
front-end-development10
build-automation10
automated-build10
command-line10
Programming languages (11)
Github contributions (5)
justindujardin/mathy
Jul 2018 - Oct 2022
Tools for using computer algebra systems to solve math problems step-by-step with reinforcement learning
Role in this project:
ML Engineer
ML EngineerContributions:26 releases, 1071 commits, 94 PRs in 4 years 3 months
Contributions summary:Justin's commits focused on developing machine learning solutions within the repository. They added new node control lessons to the curriculum, allowing users to simplify polynomials using computer algebra systems. The user also implemented functionality for balancing positive and negative rewards during training and integrated features related to user-specified training data sampling.
solvemathcomputer-algebra-systemproblemsreinforcement-learning
jashkenas/docco
Mar 2012 - Feb 2013
Literate Programming can be Quick and Dirty.
Role in this project:Back-end Developer
Back-end DeveloperContributions:101 commits, 1 comment in 11 months
Contributions summary:Justin primarily contributed to the `jashkenas/docco` repository by implementing enhancements to the build process and command-line interface. They added options for custom templates, CSS files, and output paths, indicating a focus on configurability. The user also introduced support for resolving source files and documented the public API, suggesting a role in making the tool more user-friendly and extensible. They also updated the code to support node 0.6 and 0.8.
literate-programmingdirtyprogramming-languageliterate
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