Steven Diamond

Compute Optimization Researcher

Mountain View, California, United States
email-iconphone-icongithub-logolinkedin-logotwitter-logostackoverflow-logofacebook-logo
Join Prog.AI to see contacts
email-iconphone-icongithub-logolinkedin-logotwitter-logostackoverflow-logofacebook-logo
Join Prog.AI to see contacts

Summary

🤩
Rockstar
🎓
Top School
Steven Diamond is a founder and research scientist with 13 years of experience bridging academia and industry in applied machine learning and optimization. Based in Mountain View, he holds BS, MS and a PhD in Computer Science from Stanford and has driven research roles at Gridmatic and BlackRock’s AI Labs before co-founding Optimal Intellect. He contributes to foundational open-source tooling—most notably improving documentation and MIP support for the widely used convex optimization library CVXPY—showing a knack for making complex math accessible to practitioners. Comfortable shipping research into production, he combines deep algorithmic expertise with product-minded engineering and a persistent focus on user experience. An under-the-radar strength is his sustained commitment to better docs and examples, which amplifies the impact of technical work across teams.
code13 years of coding experience
job6 years of employment as a software developer
bookDoctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at Stanford University
github-logo-circle

Github Skills (4)

documentation10
convex-optimization10
python10
api-design8

Programming languages (14)

C++LeanCRustTeXGoHTMLJupyter Notebook

Github contributions (5)

github-logo-circle
cvxpy/cvxpy

Jul 2013 - Jan 2023

A Python-embedded modeling language for convex optimization problems.
Role in this project:
userBack-end Developer & Documentation Specialist
Contributions:21 releases, 856 reviews, 393 commits in 9 years 8 months
Contributions summary:Steven's commits primarily focused on updating and improving the documentation for the CVXPY library. The user updated examples, API documentation, and installation instructions, demonstrating a commitment to improving the user experience. Further contributions involved fixing issues and adding support for mixed integer programming (MIP) problems, signifying a role in the project's core functionality and user support. The user also contributed to updating examples to be more compatible with different versions of the package.
convex-optimizationpythoncvxpyoptimizationmodeling-language
cvxpy/cvxpyanalyzer

Jul 2020 - Oct 2021

Contributions:4 reviews, 6 commits, 1 PR in 1 year 3 months
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.
Request Free Trial