Ievgen Sidenko

Petro Mohyla Black Sea National University

Papers

Total Citations

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About

Ievgen Sidenko is a researcher advancing the intersection of machine learning and robotics, with a focus on real-time control and sensor information processing. His work addresses a critical challenge in modern industry: how to make intelligent robots more efficient and responsive in dynamic environments. In his highly cited 2022 paper, "Machine Learning Techniques for Increasing Efficiency of the Robot’s Sensor and Control Information Processing," Sidenko explores how machine learning can optimize the processing of sensor data and control signals in real-time systems—including industrial automation, SCADA systems, and robotics. This work has garnered 40 citations, reflecting its relevance to practitioners seeking to improve robot mission performance. His 2021 study, "Manipulator's Control System with Application of the Machine Learning," provides a comprehensive analytical review of approaches for integrating artificial intelligence into robotic control, particularly for pattern recognition and classification tasks. Through these contributions, Sidenko bridges theoretical machine learning methods with practical, real-world robotic applications, offering valuable insights for engineers and researchers working to enhance the autonomy and efficiency of intelligent systems in industrial settings.