Charlie Vanaret

With Uno, finally take full control of your SQP/barrier solver for nonlinearly constrained optimization

Berlin, Berlin, Germany

About

Researcher in nonlinear optimization Actively developing Uno, a unified solver for nonlinearly constrained optimization: https://github.com/cvanaret/Uno (MIT license) Modern, modular and lightweight, it unifies iterative methods (SQP vs interior points) and globalization strategies (filter method vs merit function, line search vs trust region method) in a single framework. Competitive against IPOPT, filterSQP and CONOPT. My research interests include mathematical programming, global optimization, interval constraint programming, modern software development and (in the near future) optical design.

Experience

  • Researcher at Zuse Institute Berlin
    Jan 2026 - Present · 7 mos

  • Assistant computational mathematician at Argonne National Laboratory
    Mar 2024 - Dec 2025 · 1 yr 10 mos

  • Researcher at Zuse Institute Berlin
    Oct 2022 - Dec 2023 · 1 yr 3 mos

    Massively parallel interior-point method + machine learning for solving doubly bordered block diagonal mixed-integer problems

  • Researcher at Berlin Institute of Technology (Technische Universität Berlin)
    Jun 2020 - Sep 2022 · 2 yrs 4 mos

    Massively parallel interior-point method + machine learning for solving doubly bordered block diagonal mixed-integer problems

  • Researcher at Fraunhofer ITWM
    Sep 2018 - Mar 2020 · 1 yr 7 mos

    Modeling and optimization for chemical processes