Timofei Semenov is a Senior Software Engineer with 11 years of experience focused on computer vision, NLP and data science, now based in Mountain View and working on AI Data at Google. He has a track record of moving research-grade ML into production across roles at Google, Yandex and conversational-AI startup Luka, combining deep learning and engineering rigor. An active contributor to TensorFlow Datasets, he implemented the CoNLL2002 dataset and harmonized configurations with CoNLL2003, reflecting practical experience with NLP dataset standards. His academic background from Yandex School of Data Analysis and a Data Science MS underscores strong statistical foundations alongside hands-on systems work. Colleagues rely on him to bridge model development, dataset engineering and scalable backend implementation. Notably, his career shows repeated transitions between core ML research and production-focused AI data engineering, making him fluent in both experimentation and deployment.
11 years of coding experience
8 years of employment as a software developer
Master of Science - MS Data Science, Master of Science - MS Data Science at Higher School of Economics
Bachelor of Science - BS Applied Mathematics & Computer Science, Bachelor of Science - BS Applied Mathematics & Computer Science at Irkutsk State University
Master of Science - MS Data Science, Master of Science - MS Data Science at Yandex School of Data Analysis
Bachelor of Science - BS Applied Mathematics & Computer Science, Bachelor of Science - BS Applied Mathematics & Computer Science at Stony Brook University
TFDS is a collection of datasets ready to use with TensorFlow, Jax, ...
Role in this project:
Back-end Developer
Contributions:6 reviews, 23 commits, 13 PRs in 2 months
Contributions summary:Timofei implemented the CoNLL2002 dataset by adding a new dataset class and configurations. They made adjustments to existing configurations for consistency with the CoNLL2003 dataset. The changes included renaming configurations and introducing specific Part-of-Speech (POS) tags and configurations unique to CoNLL2002. These changes involved modifications to multiple files and included implementation of functionality for natural language processing tasks.
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