Jérome Eertmans
Research Intern at UCLouvain - Université catholique de Louvain
Grez-Doiceau, Walloon Brabant, Belgium
Summary
🤩
Rockstar🎓
Top SchoolJérome Eertmans is a PhD candidate and teaching assistant at UCLouvain specializing in differentiable ray tracing for telecommunications, combining deep academic research with practical software development. He has nine years of engineering experience spanning radar ray-tracing, FPGA HDL, and BLE interference mitigation, and spent a research visit at the University of Bologna working on radio propagation modeling. An active open-source contributor, he has improved core numerical functionality in the widely used Numba project and clarified CLI/config documentation in Meilisearch, reflecting attention to correctness and developer experience. He regularly builds research-grade tools in Python and MATLAB, ports and optimizes algorithms, and enjoys turning prototypes into usable software—evidenced by camera-based medical testbenches and exam-scheduling tools. Looking for postdoc or industry roles from July 2026, Jérome blends hands-on backend development, teaching experience, and a practical mindset for translating theory into reproducible code.
9 years of coding experience
Doctor of Science Telecommunications Engineering, Doctor of Science Telecommunications Engineering at Université catholique de Louvain
French, English, Dutch, Italian
Github Skills (16)
meilisearch10
compiler10
configuration-management10
compiler-compiler10
rust10
numba10
python10
documentation10
numpy10
apidoc9
command-line9
llvm9
cli9
command-line-interface9
api9
Programming languages (17)
Github contributions (5)
numba/numba
Sep 2020 - Jun 2021
NumPy aware dynamic Python compiler using LLVM
Role in this project:
Back-end Developer
Back-end DeveloperContributions:5 reviews, 14 commits, 4 PRs in 8 months
Contributions summary:Jérome primarily contributed to improving the `numba` library, a NumPy-aware dynamic Python compiler. Their work involved fixing documentation references and correcting typos in documentation. The user also updated and added support for the `np.correlate` and `np.convolve` functions, including supporting all available modes and implementing them in a manner consistent with the NumPy implementation. These modifications indicate a focus on the core functionality and user experience of the library.
compilerllvmnumpypythoncuda
meilisearch/meilisearch
Oct 2022 - Oct 2022
A lightning-fast search engine API bringing AI-powered hybrid search to your sites and applications.
Role in this project:Back-end Developer
Back-end DeveloperContributions:2 reviews, 12 commits, 2 PRs in 3 days
Contributions summary:Jérome's contributions primarily focused on enhancing the documentation related to CLI options and configurations within the Meilisearch project. Their work involved detailed updates to the `meilisearch-http/src/option.rs` file, adding and clarifying various command-line arguments, settings, and environmental variables related to the application's functionality. The commits also demonstrate the user's involvement in refining the log levels and documentation details.
aisearch-enginetypo-tolerancesite-searchdatabase
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