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Welcome to my own little plane of Oblivion! 🪐

My name is Mateus Begnini Melchiades and I am a Software Developer and Researcher in Machine Learning. My main field of study is centered around Option discovery in Reinforcement Learning, but I also work on projects related to NLP and Neural Networks. I work as a Software Developer at SAP Labs Latin America, where I develop backend services related to Data Science. I also hold a bachelor's degree in Computer Science from the University of Vale do Rio dos Sinos (UNISINOS), with an outstanding student award from the Brazilian Computing Society (SBC).

On my spare time, I use my programming skills to create and contribute to open-source projects mostly related to Linux. I spend most of this time improving Vanilla OS, which I act as Contributors Leader.

The programming languages I usually work with are (in order of familiarity):

  • Python (including popular libraries like Pandas, Numpy, PyTorch, ...)
  • Go
  • C
  • Lua
  • Bash
  • Rust
  • Vala

My creations

  • JABS.nvim: A minimal buffer switcher window for Neovim written in Lua.
  • tree-sitter-vala: A tree-sitter implementation for the Vala programming language.
  • Albius: An installer backend focused on immutable Linux distributions, but suitable for all distros (part of Vanilla OS)

Larger projects I contribute to

  • Vanilla OS Contributors Leader: I develop and improve system applications like ABroot and Apx, as well as GNOME-related projects for better integration with the OS. My role in the project also involves managing incoming contributions and making sure our applications work as expected.

Research papers I worked at:

  • Co-author of "FastIoT - A Compression Model for Displaying a Huge Volume of IoT data in Web Environments" (publication pending)
  • Main author of "Anticipating faults by predicting non-linearity of environment variables with neural networks: a case study in semiconductor manufacturing" (accepted for presentation at LXAI @ ICML 2021)
  • Co-author of "MoStress: a Sequence Model for Stress Classification" in 2022 International Joint Conference on Neural Networks (IJCNN), Padova, Italy, 2022.

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