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Achievement: Pair Extraordinairex4Achievement: QuickdrawAchievement: Pull Sharkx3Achievement: YOLOAchievement: Arctic Code Vault Contributor

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michaelellis003/README.md

Hi, I'm Michael!

Hello! I'm Michael, a data scientist with a math and statistics background who likes to build things. My work spans Bayesian methods and causal inference to LLMs, GenAI, and AI agents. I believe good data science requires good software engineering. Currently, I'm especially interested in the intersection of causal inference and agentic AI, building systems that use causal reasoning for counterfactual simulation and intervention planning.

Featured Work

  • lmxlab - Language models for Apple Silicon on MLX (docs)
  • smcx - Sequential Monte Carlo and particle filtering in JAX (docs)
  • pypkgkit - CLI tool for scaffolding production-ready Python packages (PyPI)
  • paperboy - An MCP server that organizes research papers in Zotero and sends them to your e-reader from Claude.

Open Source Contributions

A collection of open source projects I have contributed to:

Tech Stack

Python JAX NumPyro MLX PyTorch R C++ TypeScript SQL Docker uv

Connect

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  1. lmxlab lmxlab Public

    Transformer language models on Apple Silicon with MLX

    Python 1

  2. smcx smcx Public

    State-space inference in JAX: Kalman and particle filters, tempered SMC, and SMC²

    Python 3

  3. pypkgkit pypkgkit Public

    Production-ready Python package template with uv, ruff, pyright, and GitHub Actions CI/CD

    Python

  4. paperboy paperboy Public

    MCP server that delivers research papers to your e-reader — Zotero as the source of truth. Search, discover, queue, and send to Kindle/Kobo from Claude.

    Python 5 2

  5. sequential-monte-carlo-hmm sequential-monte-carlo-hmm Public

    Master's thesis: Sequential Monte Carlo methods for inference in Hidden Markov Models

  6. variational-inference variational-inference Public

    Variational Bayes and CAVI algorithms from Ormerod & Wand — approximate Bayesian inference examples in R

    R 2