Yurii Yelisieiev
About Yurii Yelisieiev
Yurii Yelisieiev is a Deep Learning Research Engineer at Respeecher in Kyiv, Ukraine, with a background in machine learning and computer vision. He has held various roles in research and development across multiple organizations and has a strong academic foundation in computer science and data science.
Work at Respeecher
Yurii Yelisieiev has been employed at Respeecher as a Deep Learning Research Engineer since 2024. He works in Kyiv, Kyiv City, Ukraine, and has been in this role for 8 months. His responsibilities include developing and researching deep learning solutions, contributing to the company's advancements in voice synthesis technology.
Previous Experience in Machine Learning
Before joining Respeecher, Yurii Yelisieiev worked at DRESSX as a Machine Learning Research Engineer from 2021 to 2022 for 6 months. He also served as a Computer Vision Research Engineer at the Ukrainian Catholic University ML Lab from 2020 to 2022 for 2 years, gaining valuable experience in both research and commercial development of machine learning solutions.
Academic Background
Yurii Yelisieiev studied at the Ukrainian Catholic University, where he earned a Bachelor of Applied Science in Computer Science. He furthered his education by obtaining a Master's degree in Data Science from the same institution. This academic foundation supports his expertise in machine learning and computer vision.
Teaching and Lecturing Roles
In addition to his research roles, Yurii Yelisieiev has been a Lecturer at the UCU Faculty of Applied Sciences / APPS UCU since 2022. He has also served as a Teaching Assistant at the Ukrainian Catholic University in various capacities from 2018 to 2021, contributing to the education and development of students in the field of data science and machine learning.
Research Interests
Yurii Yelisieiev has specific research interests in 3D Representation Modelling, 3D Machine Learning, and Geometry. These areas reflect his focus on advancing the understanding and application of machine learning techniques in three-dimensional contexts.