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AlejandroCoronadoN/README.md

Hi, I'm Alejandro 👋

Open-source contributor working across time-series forecasting, machine learning, and systems / command-line tools. I like small, correct changes backed by tests: GNU parity for Rust CLI utilities, and numerical correctness for Python ML and forecasting libraries.

  • 🔭 Contributing to: uutils (coreutils, findutils), and Python ML/forecasting (darts, sktime, tslearn, torchmetrics, xgboost).
  • 🧰 Languages: Python, Rust, TypeScript/JavaScript.
  • 🧠 Interests: time-series forecasting, computational statistics, Bayesian modeling, distributed systems, LLM/AI tooling, parsers and CLI correctness.
  • 🎓 CS background (ITAM): machine learning, algorithms, distributed systems, compiler design.

Recent merged open-source contributions

  • uutils/coreutils — uniq repeated -D (#13898), fold GNU error messages (#14056), join -o field accumulation (#14070)
  • uutils/findutils — non-UTF-8 argv (#833), -size prefix (#834), signed -maxdepth (#835), ISO 8601 dates in -newerXt (#847), doubled error prefix on -type (#849)
  • dmlc/xgboost — plot_importance value-label offset for small importances (#12497)
  • sktime/sktime — mean_squared_log_error cleanup (#10816)
  • modelscope/ms-swift — format_time rounding (#9919)
  • unit8co/darts — extract_subseries return contract (#3184)
  • tslearn-team/tslearn — LCSS Sakoe-Chiba constraint (#705)

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  • 🤝 Open to interesting open-source collaborations in ML, forecasting, and systems tooling.

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