Yelysei is a Research Engineer at Qualcomm AI Research, where he focuses on topics related to neural network quantization and compression.

Yelysei obtained his M.Sc. in CSE from the Technical University of Munich and a B.Sc. in System Analysis and Control from Kyiv Polytechnic Institute (Ukraine).

During this journey he worked on a wide range of projects in both academy and industry, spanning unsupervised learning using undirected and directed Deep Generative Models, Bayesian and probabilistic methods applied to Machine Learning and Deep Learning, Super Resolution, self-supervised algorithms for Visual Odometry and SLAM, and a little bit of NLP and Data Science.

In his Master's project, done in collaboration with Volkswagen Data:Lab, he developed a novel Quantum Machine Learning model that is physically plausible, more accurate, and much more efficient than the previous work.