Pavel Petrochenko
Founder, VP Of Technology at OnPositive Technologies
Novosibirsk Oblast, Russia
Summary
👤
Senior🎓
Top SchoolPavel Petrochenko is a seasoned software engineer and founder with over 12 years of hands-on experience and more than seven years as a software architect, currently serving as VP of Technology at OnPositive Technologies. He specializes in Java, Eclipse Platform/RCP, OSGi, compilers and parsers, and has been an active Eclipse committer and Apache contributor—work that includes JIT optimization and Design-by-Contract tooling for Apache Harmony. Pavel’s career spans IDE and RCP application development, semantic OWL/RDF applications, and model-driven development, and he continues to contribute to open-source projects such as a RAML–JAX-RS transformation tool. Based in Novosibirsk, he combines deep compiler and tooling expertise with entrepreneurial leadership, often tackling non-obvious cross-cutting problems like code generation nuances and nested schema handling that improve developer UX.
12 years of coding experience
9 years of employment as a software developer
25/AcademgorodokMaster, Information Technologies, Physics, Master, Information Technologies, Physics at Novosibirsk State University (NSU)
English
Github Skills (7)
javas10
code-generation10
raml10
java10
jax-rs10
json-schema9
maven9
Programming languages (7)
Github contributions (5)
mulesoft-labs/raml-for-jax-rs
Apr 2014 - Dec 2015
This project is all about two way transformation of JAX-RS-annotated Java code to RAML API description and back.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:1 release, 106 commits, 8 PRs in 1 year 7 months
Contributions summary:Pavel primarily contributed to the backend aspects of the RAML to JAX-RS transformation project. They addressed bug fixes, specifically related to path handling, schema property usage and other code generation aspects. Furthermore, the commits reveal modifications to core code generation, including changes to how nested schema names are handled and parameter processing.
transformationapitwo-wayjaxjax-rs
musket-ml/segmentation_training_pipeline
Oct 2018 - Nov 2019
Research Pipeline for image masking/segmentation in Keras
Contributions:1 release, 120 commits, 8 PRs in 1 year 1 month
pipelinedeep-learningimage-segmentationtensorflowkeras
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