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SoheilGtex/README.md
System trajectory from probabilistic state to deterministic state

Soheil Salmani

DevOps Engineer • Systems • Mathematics

I build deterministic systems in probabilistic environments.

Currently working in DevOps and Infrastructure at Fara-Ro, focusing on deployment reliability, application security, and CI/CD architecture. My approach is rooted in my academic background in Mathematics—treating infrastructure not merely as configuration scripts, but as state spaces governed by strict constraints, invariants, and convergence properties.

The progression of my work is deliberate:

Python Backend   ↦   Data Engineering   ↦   DevOps & DevSecOps

Every transition has been driven by the same fundamental objective: enforcing mathematical structure and reliability on complex, moving systems.


Core Domains

  • Infrastructure & Reliability: Linux, Docker, CI/CD, GitHub Actions, Automated Testing, Server Hardening.
  • Software & Data: Python, PostgreSQL, FastAPI, Data Pipelines, ETL.
  • Computational: Mathematical Modeling, Probability, Linear Algebra, Statistical Analysis.

The pinned repositories carry the implementation details.


Pinned Loading

  1. mathematical-research-intelligence mathematical-research-intelligence Public

    Mathematical research discovery with automated arXiv reports, metadata quality monitoring, and a Python-based data engineering platform.

    Python 10

  2. neuroscale-lab neuroscale-lab Public

    Reproducible EEG complexity analysis, scientific data engineering, and cross-subject workload modeling

    Python 8

  3. numerical-learning-dynamics numerical-learning-dynamics Public

    A reproducible numerical modeling study of early student-performance forecasting, numerical stability, regularization, uncertainty, and robustness.

    Python 8

  4. finance-data-pipelines finance-data-pipelines Public

    Correctness-first finance time-series ETL and SQLite benchmark with reproducible 100k/1m experiments, recovery testing, CI, and Docker.

    Python 16

  5. numerical-sine-approximation-matlab numerical-sine-approximation-matlab Public

    Numerical study of sine approximation in MATLAB using Taylor recurrences, range reduction, Chebyshev polynomials, Clenshaw evaluation, floating-point analysis, benchmarking, tests, and reproducible…

    MATLAB 11

  6. Active-Noise-Cancelling Active-Noise-Cancelling Public

    Real-time microphone noise suppression in Python (spectral subtraction + adaptive EMA, 20 ms frames, 50% OLA).

    Python 28 2