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RS-Coop/README.md

Hello, I'm Cooper Simpson

Since 2024, I am a PhD student in Applied Mathematics at the University of Washington in Seattle, where I am advised by Alexsandr Aravkin. I am also a 2025 recipient of the Department of Energy Computational Science Graduate Fellowship (DOE CSGF).

Prior to this I...

  • Worked as a professional research assistant in the Aerospace Mechanics Research Center (AMReC) at the University of Colorado Boulder from 2022-2024, where I collaborated with Alireza Doostan and Stephen Becker on data compression techniques for large-scale scientific simulations.
  • Earned my B.S. and M.S. from CU Boulder in Applied Mathematics in 2020 and 2022 respectively, where I was advised by Stephen Becker for my masters thesis on non-convex Newton-type optimization methods.

Broadly, my research interests are in computational and mathematical science. I have worked in areas such as non-convex optimization, deep learning, data compression, and algorithmic economics. I appreciate both the theory and application side of problems, which is to say I enjoy both proving a theorem and programming a software package.

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  1. QuasiNewton.jl QuasiNewton.jl Public

    A collection of Newton-type optimization algorithms implemented in Julia.

    Julia 1

  2. RandNLA.jl RandNLA.jl Public

    Julia algorithms for randomized numerical linear algebra.

    Julia 1

  3. PyTorch-ARC PyTorch-ARC Public

    Adaptive Regularization with Cubics (ARC) optimizer for PyTorch.

    Python

  4. AlgorithmicDataReduction/PyTorch-QuadConv AlgorithmicDataReduction/PyTorch-QuadConv Public

    Quadrature-based convolutions for deep learning on unstructured and non-uniform mesh data.

    Python 7 2

  5. RS-Coop.github.io RS-Coop.github.io Public

    Personal website

    HTML