Oleksandr Filipenko

Kharkiv National University of Radio Electronics

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About

Oleksandr Filipenko is a researcher at the forefront of integrating micro-electromechanical systems (MEMS) with machine learning for advanced robotics and motion analysis. His primary research areas include MEMS-based inertial sensing, robot motion classification, and the application of machine learning to sensor signal processing. Filipenko’s most notable contribution is his pioneering work on using MEMS inertial sensor signals combined with machine learning methods to classify robot motion states. In his highly cited 2018 study, he demonstrated how data from a three-axis MEMS gyroscope mounted on a robot body can be effectively used to distinguish different motion patterns. This work, which has garnered 13 citations, provides a foundational framework for developing more intelligent and autonomous robotic systems. By systematically investigating various machine learning algorithms for this classification task, Filipenko has helped bridge the gap between low-cost sensor hardware and sophisticated data interpretation. His research holds significant promise for applications in robotics, autonomous navigation, and human-robot interaction, making him a key contributor to the growing field of intelligent sensor systems.