Konstantin Lopukhin
Head Of R&D at Zyte
United Kingdom
Summary
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RockstarKonstantin Lopukhin is a senior engineering leader with 15 years of experience now heading R&D at Zyte in the UK, having progressed through machine learning and data science leadership roles within the same company. He blends deep backend Python expertise with product-focused research, contributing to prominent open-source projects like Scrapy, Twisted and dateparser where he improved Python 3 compatibility, performance and robustness. Konstantin has a track record of shipping pragmatic fixes and refactors—tests, deprecations and regex optimizations among them—that tangibly improved reliability and performance in widely used libraries. Comfortable moving between hands-on code and team leadership, he brings an unusual combination of long-term maintainership in web scraping tooling and applied ML experience to scale data-driven engineering.
15 years of coding experience
16 years of employment as a software developer
Github Skills (48)
asynchronous10
python10
python-asyncio10
async10
scikit10
testing10
http10
date-parsing10
machine-learning10
backward-compatibility10
webscraping10
headless-browser10
regular-expression10
event-driven10
scrapy10
Programming languages (11)
Github contributions (5)
scrapinghub/extruct
May 2018 - Oct 2022
Extract embedded metadata from HTML markup
Role in this project:
Back-end Developer
Back-end DeveloperContributions:37 reviews, 76 commits, 59 PRs in 4 years 6 months
Contributions summary:Konstantin made several contributions focused on improving the `extruct` library. They refactored the code, moving functionality from the `__init__` module to a new module, and also imported individual extractors. The user added tests for URL handling, and deprecated an argument, favoring the use of `base_url`. Finally, the user made various maintenance changes and prepared the release.
json-ldmicroformatsheadmeta-tagssemantic-web
TeamHG-Memex/eli5
Sep 2016 - Jan 2020
A library for debugging/inspecting machine learning classifiers and explaining their predictions
Role in this project:Data Scientist
Data ScientistContributions:2 reviews, 436 commits, 110 PRs in 3 years 4 months
Contributions summary:Konstantin primarily contributed to enhancing and maintaining the eli5 library for debugging machine learning models, specifically focusing on explaining and visualizing predictions. They added support for dense and sparse vectors, enabling the library to handle different data formats used in explainable AI. Moreover, they expanded the library's capabilities to support explaining predictions from diverse models like regressors and handling multiclass classification problems.
nlpxgboostpythoncrfsuiteinspection
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