# Eugenio "Jay" Zuccarelli

> Eugenio "Jay" Zuccarelli is an AI and machine learning engineer who builds applied AI/ML systems across the full lifecycle — from research and modeling to production deployment. He specializes in agentic AI, generative models, retrieval-augmented generation (RAG), reinforcement learning from human feedback (RLHF), and causal inference. He is an open-source contributor to the Python and Julia ecosystems.

## Identity

- Full name: Eugenio Zuccarelli
- Also known as: Jay Zuccarelli
- Website: https://eugeniozuccarelli.com/
- GitHub: https://github.com/jayzuccarelli
- LinkedIn: https://linkedin.com/in/jayzuccarelli
- X (Twitter): https://x.com/jayzuccarelli

## Focus areas

- Applied AI: agentic AI, generative models, production AI, retrieval-augmented generation, evals, RLHF
- ML modeling: supervised, unsupervised, and reinforcement learning; feature engineering; model selection; hyperparameter tuning
- Data science: experimentation, causal inference, forecasting, decision systems

## Stack

Python, PyTorch, TensorFlow, AWS, GCP, SQL, Spark, Docker, Kubernetes, Git, Linux, Bash.

## Open-source projects

- [autofill](https://github.com/jayzuccarelli/autofill): AI-powered form autofill agent built on browser-use. Describe yourself once, point it at any web form, and it fills every field automatically; the user reviews and submits manually.
- [sparseregression](https://github.com/jayzuccarelli/sparseregression): Python library implementing sparse regression for high-dimensional data with automatic feature selection. Published on PyPI with 5,000+ downloads.
- [GradientBoosting.jl](https://github.com/jayzuccarelli/GradientBoosting.jl): Julia implementation of gradient boosting for training and prediction. Registered in the official Julia package registry, installable via Pkg.jl.