Evgeny Ukhanov
About Evgeny Ukhanov
Evgeny Ukhanov is a Senior Rust Blockchain Engineer with extensive experience in software development and architecture. He holds a Ph.D. in Philosophy and has worked in various technical roles across multiple companies since 2014.
Current Role at Near Inc
Evgeny Ukhanov serves as a Senior Rust Blockchain Engineer at Near Inc. He has held this position since 2021, contributing to the development of blockchain technologies. His role involves utilizing his expertise in Rust programming to enhance the company's blockchain solutions.
Previous Experience in Blockchain Development
Prior to his current role, Evgeny Ukhanov worked at several organizations in the blockchain sector. He was a Senior Rust developer at Bitfury from 2018 to 2019 and later served as a Senior Rust/Go blockchain platform engineer at 482.solutions from 2019 to 2020. He also held the position of System Architect & Tech Lead at Decracy for five months in 2020.
Educational Background
Evgeny Ukhanov studied at V. N. Karazin Kharkiv National University, where he earned a Doctor of Philosophy (PhD) in Social Philosophy and Philosophy of History from 2005 to 2010. He also attended the National Technical University 'Kharkiv Polytechnic Institute,' achieving a Magister in Control Systems of Spacecrafts from 1999 to 2005.
Technical Skills and Expertise
Evgeny Ukhanov possesses a diverse skill set in both technical and philosophical domains. He specializes in RISC-V CPU architecture and has proficiency in cloud services, including Amazon Web Services and Google App Engine. His experience extends to designing and developing FPGA systems, microservices architecture, and high-load systems, utilizing tools such as Docker, KVM/Qemu, and Kubernetes.
Programming Languages and Database Knowledge
Evgeny Ukhanov is experienced in a variety of programming languages, including Rust, Go, F#, Haskell, Python, and WebAssembly. He has a deep understanding of database systems, including Postgres SQL, MySQL, MongoDB, MS SQL, and SQLite. His background in mathematical modeling is particularly relevant to blockchain and tokenomics.