Paul Goulart
Professor Of Engineering Science at Optimal Labs
Oxford, England, United Kingdom
Summary
🤩
Rockstar🎓
Top SchoolPaul Goulart is a Professor of Engineering Science at the University of Oxford with nine years of postdoctoral professional experience and a career bridging control engineering, aerospace, and applied optimization. He earned advanced degrees from MIT and a PhD in Control Engineering from Cambridge, and has held research and teaching roles at ETH Zurich, Imperial College London, and Harvard’s Chandra mission operations. His work combines rigorous academic leadership with hands-on systems and software development—contributing backend integrations to prominent open-source optimization projects such as CVXPY and the OSQP quadratic solver, including Clarabel solver support, SDP handling, warm starts and low-level C++ improvements. Active on industry advisory boards, he brings a pragmatic focus on solver performance and numerical robustness that informs both theoretical research and production-ready tooling. An engineer who moves comfortably between flight operations, autonomous systems, and mathematical programming, he is known for translating complex control problems into reliable computational solutions.
9 years of coding experience
17 years of employment as a software developer
MSc, Aerospace, Aeronautical and Astronautical Engineering, MSc, Aerospace, Aeronautical and Astronautical Engineering at MITPhD, Control Engineering, PhD, Control Engineering at University of Cambridge
Github Skills (16)
mathematical-optimization10
numerical-optimization10
cvxpy10
lang10
c-language10
quadratic-programming10
convex-optimization10
cprogramming-language10
python10
linear-algebra10
modeling10
optimization10
sparse-matrix9
memory-management9
unit-testing8
Programming languages (7)
Github contributions (5)
osqp/osqp
Nov 2016 - Dec 2021
The Operator Splitting QP Solver
Role in this project:
Back-end Developer
Back-end DeveloperContributions:10 reviews, 179 commits, 45 PRs in 5 years 1 month
Contributions summary:Paul primarily contributed to the development and maintenance of the OSQP solver, a QP solver. Their work involved the implementation of C++ code, specifically focusing on memory management, data structures, and matrix operations. They also made changes related to the build process, and error handling.
optimization-methodsportfolio-optimizationmodel-predictive-controloperatornumerical-optimization
cvxpy/cvxpy
Sep 2022 - Sep 2022
A Python-embedded modeling language for convex optimization problems.
Role in this project:Back-end Developer
Back-end DeveloperContributions:14 reviews, 1 commit, 4 PRs in 1 day
Contributions summary:Paul primarily focused on integrating the Clarabel solver within the CVXPY framework. This involved creating an interface for the solver, adding unit tests, and addressing code quality issues. Their work included implementing support for specific constraint types and features, such as SDPs and warm start functionality. The user contributed to the documentation and overall integration of the Clarabel solver within the CVXPY project.
pythonconvex-optimizationproblemsoptimizationconvex
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.