SV.

Stamatis Vretinaris

Computational Physicist and Research Software Engineer specializing in Numerical Relativity and High-Performance Computing.

I build scalable simulation frameworks for gravitational wave modeling and develop novel numerical methods for solving partial differential equations on complex domains.

Doctoral Researcher

Max Planck Institute for Gravitational Physics (Albert Einstein Institute) Institute for Mathematics, Astrophysics and Particle Physics, Radboud University Visiting Researcher at Perimeter Institute

Supervisors: Badri Krishnan & Erik Schnetter

Contact Me GitHub Scholar arXiv logo arXiv

# Selected Projects

SphericalSBPOperators.jl

Julia Numerical Analysis Performance Optimization

High-order numerical operators for spherical and curvilinear coordinates, enabling symmetry-reduced simulations with theoretical O(N^2) speedups and memory reductions over full 3D Cartesian discretizations.

Details GitHub arXiv Talk

ScalarWaveFVM.jl

Julia FVM

Numerical framework for scalar self force in general relativity using Finite Volume Method.

Details GitHub arXiv

Ektome

Python HTCondor Bash/Linux Git (CI/CD)

Python-based automation pipeline that processed 100,000+ simulations on HPC systems (HTCondor), with robust job orchestration and post-processing.

Details GitHub

FastTanhSinhQuadrature.jl

Julia Numerical Analysis Performance Optimization

An AVX-optimized Julia library for fast Tanh-Sinh quadrature. Achieved up to 62x speedup in 1D, 35,700x in 2D, and successful microsecond-scale convergence in 3D boundary-singular integrals where competing libraries failed to meet tolerance.

Details GitHub JOSS

PythiaBNS

Python Bayesian inference ML

Improved parameter estimation for gravitational-wave models by ~10x using physics-informed priors and machine learning.

Details GitHub arXiv PRD
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# Recent Research