Освіта
Наукові інтереси
Публікації
Курси
Освіта
Керівник освітньої програми робототехніки та викладач Факультету прикладних наук, провідний інженер Інституту фізики конденсованих систем НАН України.
Займається комп’ютерним моделюванням складних систем, сильноскорельованими електронними системами, високопродуктивними обчисленнями та embedded-розробкою. Програмує на С, С++, асемблері кількох архітектур, Python, Lua тощо. Адміністратор обчислювального кластеру ІФКС. Викладає протягом тринадцяти років.
Наукові інтереси
Моделювання складних систем, обчислювальна фізику та застосування сучасних обчислювальних технологій у науці й техніці, розвитком інженерних рішень та автоматизованих систем.
Публікації
- Karabyn, P. (2019). Performance and scalability analysis of Java IO and NIO based server models, their implementation and comparison. Bachelor’s thesis, Ukrainian Catholic University.
- Sultanov, A., Protsyk, M., Kuzyshyn, M., Omelkina, D., Shevchuk, V., & Farenyuk, O. (2022). A statistics-based performance testing methodology: a case study for the I/O bound tasks. IEEE 17th International Conference on Computer Sciences and Information Technologies.
- Dyhdalovych, O., Yaroshevych, A., Kapshii, O., Kravets, I., & Farenyuk, O. (2025). Particle filter-based BLE and IMU fusion algorithm for indoor localization. Telecommunication Systems, 88(1), 9.
- Biliaiev, M. (2021). Enabling OpenMPI workloads on bare-metal infrastructure using Kubernetes.
- Stasyuk, I., Stetsiv, R., & Farenyuk, O. (2018). Low-frequency dynamics of 1D quantum lattice gas: the case of local potential with double wells. Mathematical Modeling and Computing, 2(5), 235–241.
- Zhuravinskyi, M., Maletskyi, D., Kravets, I., Kapshii, O., & Farenyuk, O. (2023). Decentralized Provisioning Algorithm For BLE Mesh Network. IEEE 18th International Conference on Computer Science and Information Technologies.
- Fedynyak, V., Hryniv, O., Bey, B., & Farenyuk, O. (2023). Performance of the modern parallel programming approaches: a case study. IEEE 18th International Conference on Computer Science and Information Technologies.
- Pasichnyk, Y. (2022). Performance analysis of synchronous and asynchronous parallel network server implementations using the C++ language.
- Fedynyak, V., Hryniv, O., Sobkovych, O., Vey, B., & Farenyuk, O. (2021). Productivity comparison of the popular parallel programming approaches on CFD problem. IEEE 16th International Conference on Computer Sciences and Information Technologies.
- Sultanov, A., Protsyk, M., Kuzyshyn, M., Omelkina, D., Shevchuk, V., & Farenyuk, O. (2021). Comparison of performance of the popular approaches to implementing parallel crawlers. IEEE 16th International Conference on Computer Sciences and Information Technologies.
- Chernetskyi, V. (2021). Development of grid computing middleware for Android smartphones.
- Molodtsov, Y. (2021). The system for monitoring the status of servers and notifying users of an excessive use of system resources.
- Laba, Y. (2019). Wall-time based performance assessment and comparison framework.
- Dyhdalovych, O., Kuchynskyy, V., Smolkin, O., Farenyuk, O., Mandziy, V., … (2024). Applicability of neural networks for processing low-dimensional sensor data on embedded systems: case study. IEEE 19th International Conference on Computer Science and Information Technologies.
- Kravchuk, S., Farenyuk, O., & Korchynskyi, O. (2024). Kruppel-like zink finger transcription factor 10 is a novel proinflammatory transcriptional repressor… 12th Seoul Symposium on Bone Health & 36th Spring Scientific Congress of KSBMR.
- Hilei, P., Petruk, M., Korotkyi, I., & Farenyuk, O. (2024). Deep learning AMR model inference acceleration with CFU for edge systems. ICASSP 2024 – IEEE International Conference on Acoustics, Speech and Signal Processing.
- Pankevych, Y., & Farenyuk, O. (2023). High-level framework for solving systems of PDEs on distributed systems. IEEE High Performance Extreme Computing Conference (HPEC), 1–5.
- Butynets, D. (2023). Performance assessment of the different approaches to implementing network servers using C++ language.
- Pasternak, N. (2022). Memory-oriented optimization techniques in General Purpose GPU programming.
- Kuchynskyy, V. (2022). Optimizing RISC-V core for machine learning workloads.
- Dyhdalovych, O. (2022). BLE phase shift and inertial sensor fusion for indoor localisation.
- Stetsiv, R.Y., & Farenyuk, O.Y. (2021). State diagrams of one-dimensional ion conductors with the two minima local anharmonic potential for ions. Journal of Physical Studies, 25(2).
- Matsiuk, M. (2021). Recognition of continuous arm movement based on electromyography data.
- Yavorskyi, H. (2021). Implementation of the efficient truly two-dimensional artificial life simulation.
- Bratus, O. (2021). BLE Mesh Reliability Optimization using Neural Networks.
Курси
”Принципи організації комп’ютера”
“Архітектура комп’ютерних систем”
“Операційні системи”
“Сучасний С++”
“Паралельне програмування із використанням С++”