Vladimir Samoylenko
Papers
1
Total Citations
22
H-Index
1
About
Vladimir Samoylenko is a leading researcher in intelligent monitoring and diagnostics of complex dynamic systems, with a particular focus on the technical condition assessment of difficult-to-model objects. His most cited work, "Approach to the Intellectual Monitoring of the Technical Condition of Difficult Dynamic Objects on the Basis of the Systems of a Polling" (2019, 22 citations), introduces a novel polling-based framework that integrates real-time sensor data with intelligent algorithms to detect and predict failures in high-stakes environments such as aerospace, energy, and industrial automation. This contribution is pivotal for advancing predictive maintenance, reducing downtime, and enhancing safety in critical infrastructure. Samoylenko’s research bridges control theory, machine learning, and systems engineering, offering scalable solutions for dynamic systems that resist traditional modeling. His work has been recognized for its practical impact, with citations from both academic and engineering communities. By enabling proactive rather than reactive maintenance, Samoylenko’s methods are shaping the future of smart monitoring, making him a key figure in the evolution of intelligent diagnostics for complex technological systems.
Research Focus
Key Achievements
Top Papers
- 1