Dmitry Tereshchenko
Machine Learning Engineer @Qorvo, Inc.
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WORK HISTORY
Machine Learning Engineer @Qorvo, Inc.
Paris, FR
Developed a UWB (radio-based technology) measurement toolkit using C and Python, enabling collection of large datasets. Designed labeling protocols using simulated and real-world data- Built an embedded Machine Learning algorithm based on Decision Trees achieving 80% error detection- Designed, validated and deployed a CNN model using TensorFlow improving distance measurement accuracy- Built automated timeseries data pipelines on Databricks (Apache Spark, Delta Lake), reducing data preprocessing time- Researched and implemented model quantization and optimization using TensorFlow Lite, and evaluated performance on embedded targets- Conducted research activities including data analysis, algorithm development, visualization-tool development, cross-team knowledge gathering, and continuous monitoring of state-of-the-art Deep Learning and UWB publications.
EDUCATION
EPITA: Ecole d'Ingénieurs en Informatique
Master degree, Computer Science
Inha University 인하대학교
Computer and Information Sciences, General
ABOUT DMITRY TERESHCHENKO
As R&D Machine Learning Engineer, I am passionate about the transformative power of data-driven technologies. I have a strong background in software and data engineering. I\'ve worked on deep learning, machine learning and computer vision through different research as well as customer-focused projects. I also have significant experience in fullstack development. Let\'s connect and see how we can collaborate together!
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