Steven Diamond

1500 E Hamilton Ave · Campbell, CA 95008 ·

I work at Gridmatic. I did my Ph.D. in Computer Science at Stanford University under Professor Stephen Boyd. I was co-advised by Professor Gordon Wetzstein and by Professor Chris Ré. My research interests include software for optimization and applications of optimization to financial planning, as well as other use cases.


Thesis: Domain-Specific Languages for Convex and Non-Convex Optimization

For a complete list, see Google Scholar.

Domain-specific languages for optimization


Matrix-free optimization

Computational imaging

Other optimization applications



  • CVXPY is an open-source modeling framework for convex optimization in Python, with tens of thousands of individual users.

  • Major corporate CVXPY users include Tesla, Netflix, BlackRock, Two Sigma, and Intuit.

  • CVXPY has also been used to teach classes at Stanford, CMU, MIT, Berkeley, UCLA, and other universities.

Other software

  • DCCP, a CVXPY extension for difference-of-convex programming.

  • NCVX, a CVXPY extension for heuristic solution of nonconvex problems.

  • DMCP, a CVXPY extension for multi-convex programming.

  • ProxImaL, a domain-specific language for image optimization.

  •, an online visualization tool for disciplined convex programming.


Head instructor

  • Convex Optimization I, Stanford University (EE364a), Sum 2019.

  • Convex Optimization Short Course, ShanghaiTech, Shanghai, Spr 2016.


  • Convex Optimization Short Course, IMT, Lucca, Spr 2016.

  • Convex Optimization Short Course, CUHKSZ, Shenzhen, Spr 2016.

Teaching assistant

  • Convex Optimization II, Stanford University (EE364b), Spr 2019.

  • Convex Optimization I, Stanford University (EE364a), Win 2019.

  • Artificial Intelligence, Stanford University (CS221), Fall 2018.