Darius Kazemi is a seasoned software engineer with 16 years of experience and a background that includes a Mozilla Fellowship and work at Harvard's Berkman Klein Center. He contributes actively to open source, notably improving ml5.js (making web-friendly machine learning more accessible) and enhancing Mastodon's back-end with practical bug fixes and features. Comfortable across full-stack and back-end Ruby work, he focuses on robustness, documentation, and developer experience. Based in Somerville, MA, Darius blends academic and community-minded projects with hands-on engineering. He has an offbeat public persona that emphasizes real-world connection over perpetual online availability, a hint that he values human-centered technology and time well spent.
Your self-hosted, globally interconnected microblogging community
Role in this project:
Back-end Developer
Contributions:4 reviews, 9 commits, 11 PRs in 3 years 7 months
Contributions summary:Darius primarily contributed to the Mastodon back-end codebase. They addressed bug fixes and feature enhancements, including fixing type mismatches, adding an option to exclude suspended domains in the domain crawler, and implementing exclusive lists. Their work involved modifying Ruby code, particularly within the `FeedManager`, `Account`, and `List` models, and making updates to support new functionality.
Contributions:22 commits, 8 PRs, 19 comments in 13 days
Contributions summary:Darius primarily focused on improving the ml5.js library's functionality and documentation. They fixed several bugs related to the Word2Vec and LSTM modules, ensuring they conformed to documentation specifications and improved error messaging. Furthermore, the user made improvements to the website's documentation by correcting grammar errors and restructuring the experiments page. They also removed an unnecessary dependency.
imagenetdeep-learninglstmjavascriptp5xjs
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Darius Kazemi - You Could Be Outside, Or Like, Learning A Useful Skill at Seriously, What Are you Doing Looking At This