Artem Kurylev

Artem kurylev

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  • Timeline

  • About me

    Machine Learning / Computer Vision Engineer - Roadly.Inc

  • Education

    • Innopolis university

      2019 - 2021
      Master of science - ms data science 4.75

      Activities and Societies: Worked on multiple projects, dedicated to computer vision, software development, information retrieval, virtualization technologies and cloud development.

    • Volgograd state technical university

      2015 - 2019
      Bachelor of science - bs software engineering

      Implemented several study projects on Java, C++

  • Experience

    • Thomas more-hogeschool

      Feb 2018 - Apr 2018
      Intern student

      Worked on web-based application dedicated to the needs of people with intellectual disabilities , aloowing them to have better conversations

    • Eora

      Jun 2020 - Dec 2020

      * Trained algorithms for digits classification to improve quality of digital and analogue water and electricity meter reading recognition * Warped deep learning models for production usage with TorchScript and ONNX* Trained and deployed model for background removal * Successfully implemented and trained algorithm for face landmark detection and achieved metrics and quality described in the article

      • Computer Vision Engineer

        Jul 2020 - Dec 2020
      • Computer Vision Engineer Intern

        Jun 2020 - Jun 2020
    • Clofit me

      Oct 2020 - May 2022
      Computer vision engineer

      * Implemented several pipeline blocks for 2D virtual try-on, such as super resolution, landmark estimation, 2D human segmentation and clothes segmentation, trained and integrated model for 2d clothes landmark estimation. * Retrieve and preprocess data for 2d virtual try-on model training via scrapping shopping websites * Implemented several stages for auto-labelling pipeline to for continuously retraining model with Airflow * Created blending mechanism for improve quality of faceswap algorithm Show less

    • Roadly, inc.

      May 2022 - now
      Machine learning engineer

      * Setting up and maintaining data-science workspace with several GPUs for experiments and development with Kubernetes, ClearML-Server, Traefik, Minio S3 * Created several pipelines with Airflow for car driving videos processing including data preprocessing, model inference, and storage downloads/uploads * Designed Postgres + Postgis database for storing geographical data with * Created several methods for fastapi application to retrieve processed data* Fine-tuned several models based on MMCV framework to improve quality of road distress segmentation* Trained multiple Pytorch models for raveling distress severity classification* Improved performance of video processing pipelines Show less

  • Licenses & Certifications