Evgenii was born in 1994 in Bryansk, Russia, and immigrated to Israel at age 14 in the framework of the NAALE program, which offers teenagers the opportunity to complete their high school education in Israel. After serving in the IDF, Evgenii joined the Technion Excellence Program, where he pursued studies in Computer Science, Physics, and Mathematics.

During his BSc studies, Evgenii worked on researching deep learning in Alex Bronstein’s lab, and he also interned in Netanel Lindner’s group, where he explored anomalous Floquet insulators, a quantum phase with unusual properties. Evgenii graduated cum laude with a double BSc in computer science and physics-mathematics.

Evgenii began his MSc in computer science, focusing on reduced supervision in deep learning under the guidance of Alex Bronstein and Avi Mendelson. He once again graduated cum laude.

Evgenii then returned to physics to pursue his PhD under the supervision of Netanel Lindner. His primary research interest lies in strongly correlated phases, and particularly topological quantum computing, an approach that uses specific quantum phases of matter to perform noise-resistant and error-resistant quantum computations. His research encompasses both theoretical condensed matter physics, such as predicting properties of experimental systems that can likely realize the required phases, and the influence of experimentally-relevant effects like dissipation on these systems, as well as quantum information, and particularly understanding how to perform computations efficiently using topological quantum computing. In addition to his work in topological quantum computing, Evgenii also seeks to apply his experience in machine learning to developing new numerical tools for studying quantum many-body problems.