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Focusing
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Focusing
19 followers · 24 following

Achievements

Achievement: Pair ExtraordinaireAchievement: StarstruckAchievement: Pull Sharkx2Achievement: Arctic Code Vault Contributor

Achievements

Achievement: Pair ExtraordinaireAchievement: StarstruckAchievement: Pull Sharkx2Achievement: Arctic Code Vault Contributor

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Jac-Zac/README.md

Jac-Zac ⌘

I'm a Master's student in Data Science & AI with a focus on deep learning and mechanistic interpretability. I have several repos covering different projects for both personal interest and research. More about me on my website.

More Information About Me 🔎 

 id && whoami && uname -a
Learn More About Me 🧐 > I try to keep up-to-date with major ML and DL papers while learning more every day.
  • 🤖 I'm currently doing a master's in Data Science & AI at the University of Trieste.
  • 🧠 Former SPAR Research Fellow (Spring 2026) — I worked on implicit personalization, probing the persona vectors LLMs build of their users.
  • 🔭 Currently working on mechanistic interpretability of Mixture-of-Experts models (expert specialization in OLMoE and GPT-OSS).
  • 🌱 I've also written hand-optimized self-attention kernels in CUDA, OpenMP, and SIMD.
  • 💬 Ask me about anything tech-related / ML / DL (if you ask me something I can't answer, that's great — it means I'll learn 📚).
  • 🤝 I'm open to collaborating on research in deep learning / mech interp — reach me at jaczac2002@gmail.com.

I try to always keep myself busy with something. I guess this kind of shows it...

Jac-Zac's activity graph

🪴 Things I like, such as editors and languages:

Skills: Neovim, PyTorch, Python, Bash, C

Pinned Loading

  1. implicit-personalization/persona-vectors implicit-personalization/persona-vectors Public

    Building pipeline for extracting steering vectors.

    Python

  2. BayesianFlow BayesianFlow Public

    This is the final project for the Probabilistic Machine Learning and Deep Learning course. In this project, we explore, analyze, and re-implement the methodology presented in the paper:

    Jupyter Notebook

  3. Self_Attention_Kernels Self_Attention_Kernels Public

    This project implements Causal Multi-Head Self-Attention (CMHSA) with three backends: a single-threaded CPU version, a multi-threaded CPU version, and a GPU-accelerated version.

    Cuda 2

  4. Stat_Missing_Data_Project Stat_Missing_Data_Project Public archive

    This project focuses on analyzing Missing data patterns using simulated datasets. And then extending the research to a real dataset

    HTML 1

  5. ML_Project_LoRA ML_Project_LoRA Public archive

    LoRA implementation in Tinygrad

    Python 2

  6. micrograd_cpp micrograd_cpp Public archive

    An implementation of https://github.com/karpathy/micrograd in c++

    C++ 1