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newtonraphson14/README.md

Ikbar Faiz

Astrophysics x Computing

Second-year Computer Science student at BINUS University working across astrophysics, machine learning, data processing, and cloud infrastructure. My work sits between scientific analysis and technical execution, with a particular focus on stellar clusters, survey-based data, scalable workflows, and computational approaches to physical questions.

I like building things that move cleanly from raw data to usable systems, whether that means processing data, training models, designing cloud infrastructure, or turning research workflows into something more rigorous and reproducible.

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Focus Areas

  • Astrophysics and survey-driven data analysis
  • Machine learning and scientific computing
  • Data processing and reproducible workflows
  • Cloud infrastructure and automation

Languages and Tools

Python NumPy Pandas scikit-learn Jupyter AWS Azure Docker Bash Git

Stats

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  1. ruwe-radial-ks-clustering ruwe-radial-ks-clustering Public

    Open-cluster RUWE radial KS analysis with membership inference and CMD workflows

    Jupyter Notebook

  2. t-crb-project t-crb-project Public

    Photometry and raw-image analysis pipeline for T Coronae Borealis using AAVSO, ASAS-SN, PS1, Legacy Survey, DASCH, and ZTF workflows.

    Python

  3. rubin-sampling rubin-sampling Public

    Public Gaia-to-ZTF baseline pipeline for variable-star period recovery, alias analysis, and Rubin-like cadence experiments.

    Python