Mariya Volkova

Kharkiv National University of Radio Electronics

Papers

Total Citations

H-Index

About

Mariya Volkova is a leading researcher at the intersection of microelectromechanical systems (MEMS), robotics, and machine learning. Her work focuses on developing intelligent methods for interpreting sensor data to understand and control robotic motion. In her most-cited paper, "MEMS-Based Inertial Sensor Signals and Machine Learning Methods for Classifying Robot Motion" (2018, 13 citations), Volkova pioneered a novel approach that combines signals from a three-axis MEMS gyroscope with advanced machine-learning algorithms to classify robot states. This foundational study demonstrated how low-cost, compact MEMS sensors could be transformed into powerful tools for real-time motion analysis, moving beyond simple measurement to enable robots to "understand" their own movement patterns. By experimentally validating various classification methods, Volkova provided a critical proof-of-concept that has influenced subsequent work in autonomous navigation and human-robot interaction. Her contributions bridge the gap between hardware miniaturization and computational intelligence, offering practical pathways for making robots more responsive and context-aware. Volkova’s research continues to shape how engineers integrate sensing and learning for smarter, more adaptive robotic systems.