Dennis Ogiermann
Doctoral Student at Chair for Continuum Mechanics, Ruhr University Bochum
Bochum, North Rhine-Westphalia, Germany
Summary
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Rockstar🎓
Top SchoolDennis Ogiermann is a doctoral student and computer scientist with a decade of experience applying numerical methods and software engineering to computational cardiology and continuum mechanics. Based at Ruhr University Bochum, he combines academic research with hands-on development—contributing to the widely used MFEM C++ finite element library by implementing error estimators, handling flux/face integrals, and adding unit tests. His background spans sensor fusion, nonlinear filtering, 3D reconstruction, and robot-based additive manufacturing, reflecting a strong focus on numerical algorithms, simulation pipelines, and practical tooling. As co-founder of NydusOne, he brings entrepreneurial drive to translate research prototypes into deployable systems.
10 years of coding experience
4 years of employment as a software developer
Master of Science - MS, Computer Science, Master of Science - MS, Computer Science at Ruhr University Bochum
German, English
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (7)
finite-element-analysis10
c-language10
hpc10
parallel-computing10
cprogramming-language10
computational-science10
scientific-computing9
Programming languages (9)
Github contributions (5)
mfem/mfem
Dec 2019 - Oct 2022
Lightweight, general, scalable C++ library for finite element methods
Role in this project:
Back-end Developer
Back-end DeveloperContributions:138 reviews, 114 commits, 12 PRs in 2 years 10 months
Contributions summary:Dennis contributed to the MFEM library by implementing and modifying error estimators for finite element methods. Their work involved fixing synchronization issues in a miniapp and implementing the base functionality for the Kelly error estimator, including the handling of fluxes, face integrals, and element error contributions. The user also modified an example to showcase the newly implemented error estimator. They further added the functionality for custom element coefficient computation and added a basic unit test to ensure the correct functionality of the implemented code.
c-plus-plusfinitefemamrc-library
termi-official/OrdinaryDiffEq.jl
Mar 2023 - Dec 2024
High performance ordinary differential equation (ODE) and differential-algebraic equation (DAE) solvers, including neural ordinary differential equations (neural ODEs) and scientific machine learning (SciML)
Contributions:27 pushes, 13 branches in 1 year 9 months
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