Ondrej Bojar
Researcher at Charles University
Prague, Czechia
Summary
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Rockstar🎓
Top SchoolOndrej Bojar is a seasoned researcher and software engineer based in Prague with 14 years of experience focused on natural language processing and machine translation. He has long-standing affiliations with Charles University and the UFAL research group, blending academic rigor with practical system work since the early 2000s. Ondrej contributes to prominent open-source MT tooling such as the Moses decoder, often handling complex branch integrations and conflict resolution to keep large codebases coherent. His strengths lie in back-end engineering for research-grade software, ensuring reproducible builds and stable toolchains that support experimental workflows. Colleagues rely on him for bridging research prototypes and production-ready components, a skill honed by years of maintaining shared code in collaborative projects. He pairs deep technical mastery with an academic perspective that prioritizes clear, maintainable implementations for long-lived research infrastructure.
15 years of coding experience
Charles University
Github Skills (8)
merge10
machine-translation10
git-merge10
conflict-resolution10
cprogramming-language9
c-language9
configuration-management8
makefile8
Programming languages (16)
Github contributions (5)
moses-smt/mosesdecoder
Aug 2011 - Apr 2017
Moses, the machine translation system
Role in this project:
Back-end Developer
Back-end DeveloperContributions:31 commits, 3 pushes in 5 years 8 months
Contributions summary:Ondrej's commits primarily involve merging branches and resolving conflicts within the Moses decoder project. These merges include integration of changes from the trunk branch into the "miramerge" branch. The user addresses conflicts in various files, including configuration, source code, and scripts related to the Moses machine translation system. The commits point towards someone working on merging or integrating different code branches, resolving conflicts, and ensuring the system compiles correctly.
machine-translation
ELITR/SLTev
Jan 2020 - Jun 2021
SLTev is a tool for comprehensive evaluation of (simultaneous) spoken language translation.
Contributions:42 commits, 4 PRs, 37 pushes in 1 year 4 months
nlptranslationevaluationspoken-languagelanguage-translation
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