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@JuliaSmoothOptimizers @JuliaOptimizationVariationalAnalysis @jso-docs @SolverStoppingJulia

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tmigot/README.md

Hi there 👋


Tangi Migot's github stats

Computational Scientist

... specializing in solving challenging mathematical problems and their practical applications. I use optimization in diverse applications such as game theory and geochemistry. An important aspect of my research is to make algorithms accessible and competitive for large-scale problems encountered in machine learning, earth sciences, and life sciences 🌱. I am also passionate about (open-source) coding and promoting science. You will mostly find me in the   Julia Language   ecosystem these days.

🔭 I am always open to new collaborations and opportunities, so feel free to reach out!


I am an active contributor to the organization JuliaSmoothOptimizers an open-source organization in the Julia programming language for linear algebra and nonlinear continuous optimization that offers the flexibility, power, and ease of use for studying numerical methods, researching new algorithms, and exploring new ideas. Apart from my contributions to the 76 (!) Julia packages of the organization, I also write tutorials and news on the organization's website.

If you are not familiar with JSO, the following packages are good starting points: ADNLPModels.jl, JSOSuite.jl, OptimizationProblems.jl.

As a part of my research project at IVADO/Polytechnique Montreal, I was interested in developing packages to model PDE-constrained optimization problems and implement solvers for such problems, see, for instance, PDENLPModels.jl, DCISolver.jl, FletcherPenaltySolver.jl, AdaptiveRegularization.jl, PDEOptimizationProblems.


I am the founder of JOVA a GitHub open-source organization of Julia packages designed to model and solve challenging problems such as complementarity problems, (quasi)-variational inequalities, optimization models with degenerate constraints, bilevel optimization models, Nash equilibrium problems, etc. It contains packages to model the problems, state-of-the-art and novel solvers, set of problems.

The organization is at an early stage and is still recruiting collaborators. A first step in the creation of this organization is the upload of the codes used in my recent research papers.


I am the main developer of SolverStoppingJulia a Github organization whose main package is Stopping.jl, a Julia package that offers a framework to implement iterative algorithms and tools to ease the uniformization of stopping criteria in iterative solvers. Check out the docs that contains plenty of tutorials and examples.

Stopping is used in several packages: AdaptiveRegularization.jl, FletcherPenaltySolver.jl, or RandomLinearAlgebraSolvers.jl.


⚡ Fun fact: I am also a furious chess player 😄.

Pinned Loading

  1. JuliaSmoothOptimizers/OptimizationProblems.jl JuliaSmoothOptimizers/OptimizationProblems.jl Public

    Optimization Problems for Julia

    Julia 88 48

  2. JuliaSmoothOptimizers/PDENLPModels.jl JuliaSmoothOptimizers/PDENLPModels.jl Public

    A NLPModel API for optimization problems with PDE-constraints

    Julia 20 5

  3. JuliaSmoothOptimizers/DCISolver.jl JuliaSmoothOptimizers/DCISolver.jl Public

    Julia 16 5

  4. JuliaSmoothOptimizers/FletcherPenaltySolver.jl JuliaSmoothOptimizers/FletcherPenaltySolver.jl Public

    Fletcher's penalty method for nonlinear optimization models

    Julia 9

  5. SolverStoppingJulia/Stopping.jl SolverStoppingJulia/Stopping.jl Public

    A framework to implement iterative algorithms

    Julia 12 3

  6. PDEOptimizationProblems PDEOptimizationProblems Public

    A list of optimization problems in PDENLPModel format

    Julia 5 1