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Angelos Katharopoulos

One of the four initial developers of MLX, Apple's array framework for machine learning on Apple silicon

  • Member of the Machine Learning Research group, Apple12

Angelos Katharopoulos works in the Machine Learning Research group at Apple. The MLX README names Katharopoulos as one of the four people who initially developed the MLX software suite, an array framework for machine learning on Apple silicon. Katharopoulos still writes code for the project; 2026 commits to the MLX repository include work on JACCL, the MLX distributed backend for low-latency communication between Macs using RDMA over Thunderbolt.12345

Work

  • MLX

    Credited in the README, together with Awni Hannun, Jagrit Digani, and Ronan Collobert, with the initial development of the MLX software suite, and listed among the authors in its citation entry. Katharopoulos continues to author commits to the repository, including to the JACCL distributed backend.345

    Project page (external site: github.com)

This profile covers public professional work only, from the sources below. It is not an endorsement or a ranking. To correct or remove it, use the correction form.

Sources · reviewed Oct 1, 2026

  1. 1.
    Angelos Katharopoulos — homepage (external site: angeloskath.github.io)

    Angelos Katharopoulos · Official page · accessed Oct 1, 2026 · evidence reviewed Oct 1, 2026

  2. 2.
    angeloskath (Angelos Katharopoulos) on GitHub (external site: github.com)

    GitHub · Official page · accessed Oct 1, 2026 · evidence reviewed Oct 1, 2026

  3. 3.
    ml-explore/mlx README (external site: github.com)

    Apple (ml-explore) · Repository · accessed Oct 1, 2026 · evidence reviewed Oct 1, 2026

  4. 4.
    ml-explore/mlx commits authored by angeloskath (external site: github.com)

    Apple (ml-explore) · Repository · accessed Oct 1, 2026 · evidence reviewed Oct 1, 2026

  5. 5.
    MLX documentation — Distributed communication (external site: ml-explore.github.io)

    Apple (ml-explore) · Documentation · accessed Oct 1, 2026 · evidence reviewed Oct 1, 2026

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