Onur Çelebi
L2 High Performance Programming Engineer at Baryonic Space
Earth, Texas, Turkey
Summary
🤩
Rockstar🎓
Top SchoolOnur Çelebi is an avionics and high-performance programming engineer with 14 years of engineering experience, currently focused on safety-critical DO-178C DAL A software and high-performance systems at Baryonic Space. He brings hands-on expertise in C99/MISRA C, avionics buses (ARINC429, MIL-STD-1553), requirements engineering with DOORS, and test automation pipelines using Jenkins and Xilinx toolchains. At ESEN he led software design, requirements reviews and test infrastructure improvements for RNE projects, and earlier implemented radar algorithms on FPGA using Verilog/VHDL. An active contributor to prominent open-source NLP and text-processing projects (e.g., facebookresearch/LASER and fastText), he has improved sentence-splitting, normalization, and fasttext evaluation/reporting, showing a rare blend of embedded avionics rigor and backend text-processing craftsmanship. Based in Texas and originally from Turkey, he pairs a dual background in electrical and computer engineering with a practical focus on delivering auditable, safety-critical systems.
14 years of coding experience
2 years of employment as a software developer
Bachelor's degree - Minor, Computer Engineering, CGPA; 3.24/4.00 Honor Student, Bachelor's degree - Minor, Computer Engineering, CGPA; 3.24/4.00 Honor Student at Atılım Üniversitesi
İngilizce
Stackoverflow
333reputation
83kreached
5answers
7questions
Github Skills (22)
c-language10
python10
machine-learning10
text-processing10
nlp10
cprogramming-language10
algorithms9
unicode9
computer-engineering9
apidoc8
api8
regular-expression8
django-orm6
excel6
grid6
Programming languages (5)
Github contributions (5)
facebookresearch/fastText
Sep 2018 - May 2020
Library for fast text representation and classification.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:3 releases, 64 commits, 5 PRs in 1 year 8 months
Contributions summary:Onur primarily focused on enhancing the `fasttext` library's functionality. Their contributions included merging and modifying dictionary-related functions, such as `computeSubwords`, to improve efficiency and flexibility. Furthermore, the user adhered to specific C++ coding style guidelines and implemented code changes to display precision/recall scores for individual labels, signifying a focus on improving the evaluation and reporting capabilities of the library. These changes were also reflected in the python bindings.
classifierbertword-embeddingsword2vectopic-modeling
facebookresearch/LASER
Apr 2022 - Jul 2022
Language-Agnostic SEntence Representations
Role in this project:Back-end Developer
Back-end DeveloperContributions:10 commits, 8 pushes, 3 comments in 3 months
Contributions summary:Onur focused on developing and refining sentence splitting and cleaning functionalities within the `facebookresearch/laser` repository. Their contributions primarily involve modifying the `sentence_split.py`, `cleaner_splitter.py`, and `remove_non_printing_char.py` files, which suggests a focus on text processing and normalization. They implemented and integrated various sentence splitting algorithms, including Moses, Indic, LaoNLP, and others, while also adding demojization and Unicode category removal features. These modifications aimed to improve the accuracy and robustness of sentence segmentation.
nlpsentencerepresentationsagnosticsentence-embeddings
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