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Ezistas Batururimi

Data Scientist & SWE

Stas Batururimi is a highly skilled professional currently immersed in the world of big data infrastructure, utilizing the Hadoop ecosystem to create and manage algorithms and solutions that leverage Machine Learning and Deep Learning. With a laser focus on AI applications in steelmaking processes like automated surface inspection and quality prediction modeling, Stas's expertise shines through his work. Notable achievements include building an Automatic Number Plate Recognition (ANPR) System for the Russian Ministry of Transport, employing Computer Vision and Neural Networks. Stas is deeply committed to quality and user experience, with a profound passion for Deep Learning and Computer Vision, continuously expanding his knowledge and refining his abilities. Dedicated to enhancing efficiency in coding, Stas employs Machine Learning to tackle business challenges and has spearheaded various Deep Learning projects utilizing cutting-edge techniques like RNN, GANs, Transfer Learning, Autoencoders, and Semi-supervised learning. With a Master of Science in Applied Mathematics and Computer Science from the Moscow Power Engineer Institute, Stas's skill set encompasses Self-Driving Cars, Spark and Hadoop ecosystem, Deep Learning and Machine Learning, iOS and Android app development, server development, and more. As an active contributor to the tech community, Stas has left a mark through projects like the ANPR system for the Russian Ministry of Transport and the Audio guide and pathfinding solution for the Hermitage museum, which achieved a top ranking upon release. His open-source contributions can be found on GitHub at https://github.com/sbatururimi.

Ezistas Batururimi
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Location

Moscow, Russia