Salim Belhaddad is a seasoned software engineer and entrepreneur with nine years of experience building AI-driven products and predictive models from France. He founded behavioral marketing and research ventures, applying consumer and applied neuroscience to drive data-informed decisions while also running pro bono projects that blend education and AI. Currently developing an AI-powered tutoring app that helped his 7-year-old reach K-12+ math proficiency, he combines hands-on engineering with practical validation in real-world learning contexts. An active open-source contributor, he has improved NetworkX documentation and fixed parsing and graph conversion bugs in a widely used Python graph library. Salim mentors students through Stanford, University of Toronto, and deeplearning.ai programs and has a track record of NDAs and sensitive research collaborations. His background in mathematics and computer science from Université Paris 13 underpins a pragmatic, research-minded approach to productizing advanced algorithms.
8 years of coding experience
10 years of employment as a software developer
MIAS Mathematics and Computer Science, MIAS Mathematics and Computer Science at Université Paris 13
Contributions:2 reviews, 9 commits, 24 PRs in 1 year 9 months
Contributions summary:Salim primarily contributed to improving the documentation and codebase of the NetworkX library. They fixed typos in docstrings, improved the descriptions of core methods within the graph class, and added documentation for a graph view. Furthermore, the user addressed issues related to parsing GraphML files and fixed a bug in the `to_directed` function. They also updated the contributor list and made changes to the `algorithms` module and its imports.
Contributions:33 pushes, 24 branches in 4 years 6 months
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Salim Belhaddad - Inducted Member at Stanford University