Ekaterina Pleshakova

MIREA - Russian Technological University

Papers

Total Citations

H-Index

About

Ekaterina Pleshakova is a leading researcher at the intersection of artificial intelligence, cybersecurity, and industrial robotics. Her work focuses on developing machine learning methods to secure robotic systems against emerging cyber threats, a critical area as automation becomes ubiquitous in manufacturing and logistics. Her most-cited paper, "Machine learning methods for the industrial robotic systems security" (2023), with 23 citations, introduces novel approaches for anomaly detection and intrusion prevention in robotic control systems, addressing vulnerabilities that could disrupt production lines or compromise safety. This contribution has been recognized as foundational for the growing field of industrial cyber-physical security. Pleshakova’s research is notable for its practical impact, bridging theoretical ML advances with real-world industrial applications. She has also contributed to the development of adaptive algorithms that enable robots to self-diagnose and respond to attacks in real time. Her work is widely cited by engineers and cybersecurity specialists, and she is frequently invited to speak at conferences on AI safety and industrial automation. For students and researchers, Pleshakova’s career exemplifies how machine learning can be harnessed to protect the critical infrastructure of the future.