Denys Rybalka is a Senior Consultant and software engineer with nine years of experience blending research-grade physics and practical software craftsmanship, now based in Dresden. He holds a PhD in Physics and has transitioned complex scientific modeling into production-grade tools, from MPI-parallel lattice Boltzmann simulations to Kubernetes-deployed Java Spring Boot services. At TNG he led legacy modernization efforts—CI/CD migrations to GitHub Actions, AWS Kubernetes deployments—and ran functional programming workshops that reflect his taste for elegant, simple solutions. An active open-source contributor, he improved SymPy’s tensor module and documentation, bringing clarity to the Butler-Portugal algorithm and adding robust constructors for tensor symmetry. He enjoys experimenting with AI, teaching others, and hacking on projects with his dog Wuki, a detail that hints at a collegial, curious person behind the code.
9 years of coding experience
8 years of employment as a software developer
Doctor of Philosophy - PhD, Physics, Doctor of Philosophy - PhD, Physics at Arizona State University
Master's degree, Physics, Master's degree, Physics at Taras Shevchenko National University of Kyiv
Contributions:20 commits, 10 PRs, 23 comments in 4 months
Contributions summary:Denys contributed to the `sympy/sympy` repository by improving the documentation and structure of the tensor module, specifically addressing the Butler-Portugal algorithm. Their work involved editing code and re-structuring documentation, as seen in multiple commits focused on clarifying and refining explanations within the `tensor_can.py` and `tensor/tensor.py` files. Furthermore, the user added constructors for `TensorSymmetry`, deprecating the `tensorsymmetry()` method and contributing to code refinement.
Contributions:156 pushes, 1 branch in 2 years 5 months
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