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svretina/README.md

Stamatis Vretinaris 👋

Computational Physicist · Research Software Engineer (HPC & Numerical Methods)

Finishing my PhD at the

Max Planck Institute for Gravitational Physics (Albert Einstein Institute) and

IMAPP @ Radboud University Nijmegen

(supervisors: Erik Schnetter, Badri Krishnan).

I turn high-level physics into scalable, reliable simulation software, from numerical method design to HPC automation and performance.

📍 Nijmegen, NL & Leipzig, DE
🌐 https://svretina.github.io/
✉️ stamatis.vretinaris@aei.mpg.de · svretina@gmail.com


Featured projects

Ektome -- HPC automation at scale

Python-based automation pipeline that processed 100,000+ simulations on HPC systems (HTCondor), with robust job orchestration and post-processing.
Stack: Python · HTCondor · Bash/Linux · Git (CI/CD)
🔗 https://github.com/svretina/Ektome

PythiaBNS -- Faster GW parameter estimation

Improved parameter estimation for gravitational-wave models by ~10× using physics-informed priors and machine learning.
Stack: Python · Bayesian inference · ML
🔗 https://github.com/svretina/PythiaBNS
📄 arXiv: https://arxiv.org/abs/2501.11518 · PRD: https://journals.aps.org/prd/abstract/10.1103/g1qs-j74x


Research & methods (current / in preparation)

  • Summation By Parts (SBP) operators for spherical symmetry
    Novel finite-difference operators with stability/accuracy validation. Implementation currently private until submission.
  • Self-force as an initial value problem (Julia framework)
    New numerical framework for self-force calculations using 3D Finite Volume + Finite Difference methods (in progress; private until submission).

What I’m strong at

  • HPC & scalability: Slurm workflows, automation pipelines, scaling studies, reproducible execution on clusters
  • Performance engineering: profiling/benchmarking (e.g., LIKWID), optimization-informed development
  • Numerical methods: FVM/FDM, stability + convergence analysis, high-order methods (DG in progress)
  • Research software engineering: Git + CI/CD, maintainable codebases, documentation-first tooling

Technical stack

  • Languages: Julia · Python · C/C++ · Fortran · Bash · Mathematica
  • Parallel / HPC: Slurm · OpenMP · Linux toolchains · performance tooling (LIKWID)
  • Methods: Finite Volume · Finite Difference · Bayesian inference · Monte Carlo

Publications & links


Open to opportunities

I’m interested in Research Software Engineer / Computational Scientist roles (HPC, numerics, scientific ML) in academia or industry.

Pinned Loading

  1. FastTanhSinhQuadrature.jl FastTanhSinhQuadrature.jl Public

    Fast and high-precision numerical integration using Tanh-Sinh (Double Exponential) quadrature in Julia.

    Julia 14

  2. GridFunctions.jl GridFunctions.jl Public

    A package that provides functionalities to work with Functions on a Grid

    Julia 3

  3. Ektome Ektome Public

    Python framework for automating the lifecycle of Einstein Toolkit simulations on HTCondor clusters, featuring robust pre-processing, asynchronous job monitoring, and scalable post-processing pipeli…

    Python 1

  4. PythiaBNS PythiaBNS Public

    PythiaBNS: Robust BNS Post-Merger Parameter Estimation with Empirical Priors

    Python 2 2

  5. TidalHorizons TidalHorizons Public

    A Python package to analyze Black Hole Horizon data with Spherical Harmonics

    Gnuplot

  6. nougat-mcp nougat-mcp Public

    MCP server for Meta's nougat-ocr. Instruct your agent to convert academic papers to Markdown files with high mathematical accuracy

    Python 3